text:
Is 2020 the year FDA will finally make CBD a legal ingredient in dietary supplements and food? 2020 Ingredient trends to watch for foods, drinks, and dietary supplements
Jennifer Grebow
Jennifer Grebow is editor-in-chief of Nutritional Outlook.
Nutritional Outlook, Nutritional Outlook Vol. 23 No. 1, Volume 23, Issue 1
CBD is out of the bottle. How will FDA rein in the skyrocketing CBD market?
Is 2020 the year FDA will finally make CBD a legal ingredient in dietary supplements and food? No one (but FDA) knows. And this is where we find ourselves yet again at the start of 2020 when it comes to hemp cannabidiol (CBD), today's biggest ingredient disruptor: with many questions and few answers.
But first: What a year it's been for CBD. Since President Trump signed the 2018 Farm Bill into law in December 2018, legalizing industrial hemp as an agricultural crop-with hemp defined as cannabis containing less than 0.3% tetrahydrocannabinol (THC) content-and removing it from Schedule I of the Controlled Substances Act, the CBD products market has exploded. Today, CBD is infused in everything from hair gel and toothpicks to personal lubricant, hand sanitizers, and even bed sheets.1
Despite being sold on shelves and online, CBD dietary supplements and food are still not legal according to FDA. For dietary supplements, FDA's primary reasoning for why CBD can't be a legal dietary supplement ingredient is that before CBD was ever sold as a dietary supplement, it was first publicly researched as an investigational new drug (IND) by GW Pharmaceuticals. This means that, under the Federal Food, Drug, and Cosmetic Act's "IND exclusion clause," CBD is ineligible to meet the definition of a dietary supplement under the Act's Section 201(ff)(3)(B)(i) and 201(ff)(3)(B)(ii).
Last year saw many try to get FDA to forge a legal pathway for CBD products. Last October, dietary supplement and natural product associations-the American Herbal Products Association (AHPA), the Council for Responsible Nutrition (CRN), the Consumer Healthcare Products Association (CHPA), and the United Natural Products Alliance (UNPA)-sent a joint letter asking Congress to create legislation to create a waiver for CBD under the definition of a dietary supplement (FD&C Act Section 201(ff)(3)) that would specifically authorize legal use of CBD in supplements. The Natural Products Association (NPA), meanwhile, was involved in pushing forth an amendment to a House spending bill last June that would have had FDA perform a Health Hazard Evaluation of CBD and ultimately set a safe usage level for consumers. The amendment language, which made it through the House bill, was unfortunately ultimately excluded in the version of the spending bill passed by the Senate.
Federal and state lawmakers, as well as state attorneys general, have also asked FDA to provide either more oversight over CBD, set a safe usage level, or to at least adopt a policy of enforcement discretion for CBD products. Notably, last September, Senate Majority Leader Mitch McConnell (R-KY) added report language to the 2020 spending bill to require FDA movement on CBD. The ultimate 2020 spending bill that President Trump signed last December requires that FDA, within 60 days, update Congress on its progress in developing a policy for enforcement discretion for CBD, and within 180 days, evaluate the market to determine the scope of CBD products that are mislabeled or making illegal claims.
But enforcement discretion does not make CBD legal in supplements; it merely means that FDA will exert discretion in how it enforces against CBD companies. And so the supplements industry is still seeking a true legal pathway forward for CBD.
The two potential pathways most commonly discussed are: 1) to somehow create a regulatory exception for CBD in Section 201(ff)(3) of the FD&C Act that would include CBD within the legal definition of a dietary supplement, or 2) to see the Secretary of the U.S. Department of Health and Human Services promulgate a new regulation for CBD specifically declaring CBD as both a legal dietary supplement and/or food ingredient.
This January, a newly proposed bill opted for the first pathway (carving out an exemption for CBD in the FD&C Act's definition of a dietary supplement). Proposed by House Agriculture Committee Chairman Collin Peterson (D-MN), the bill would essentially ensure that the IND exclusion clause in Section 201(ff)(3)(B)(i) and 201(ff)(3)(B)(ii) does not pertain to CBD. For instance, under the text stating that a dietary supplement is not "an article authorized for investigation as a new drug…," Representative Peterson's bill would add the phrase "other than hemp-derived cannabidiol or a hemp-derived cannabidiol containing substance."
Whether this bill will pass is anyone's guess. "What makes it really hard to say is [that] we are kicking off an election year," says attorney Kevin Bell, partner, Arnall Golden Gregory LLP (AGG; Washington, DC). "If anything is going to get done with it, it would need to move faster than in a non-election year. At some point, you're going to reach the middle of the year, and legislators-that's not going to be what the focus is going to be on in an election year because you don't know what's going to change, not only from the general election, but also how that might affect committees and things like that."
While some welcome the Peterson bill, the regulatory route it takes-having Congress dictate a narrow exemption for CBD supplements in the IND exclusion clause-isn't necessary most optimal, some say.
"We would have preferred to see FDA do this on its own using that discretion that's under 21 U.S.C. § 321(ff)(3)," says Steve Mister, president and CEO of the Council for Responsible Nutrition (CRN; Washington, DC). (Editor's note: 21 U.S.C. § 321(ff)(3) is the same provision, but codified, as the FD&C Act's 201(ff)(3) provision.) "That would have been the preferred way to market because then FDA would have more say in what the exclusion looks like. But given what we're seeing out of FDA, which seems to be inaction, and the larger environment around it-all the things that are happening in the face of FDA's inaction-we think this is a good alternative."
"I think [the Peterson bill] is interesting, but it's a little drastic," says Robert Durkin, of counsel, Arnall Golden Gregory LLP (AGG; Washington, DC). Durkin is the former deputy director for FDA's Office of Dietary Supplement Programs. "The agency could help the Secretary do basically the same thing if the Secretary were to promulgate a regulation…I think a better option would be for the Secretary to promulgate a regulation."
Why? "Well, what [a new regulation] does is it establishes a precedent and a paradigm for the agency to do this in the future if it has to," Durkin says. "They wouldn't have to wait for a legislative fix. And, it's really likely that CBD is not the only dietary ingredient to be affected like this. It's a solution that can be used in the future."
It's also important to note that, by only amending the definition of a dietary supplement, Rep. Peterson's bill would still not create a legal pathway for CBD in food, leaving a now quickly growing segment of the CBD market still illegal. "Food would still be in the same trap," Durkin says. But, say some, leaving CBD out of food might just be FDA's preference. "They'd much rather have this in dietary supplements than conventional food," he adds.
"I think FDA has some real concerns about [CBD in food] that make it different than supplements," says Mister. "Because supplements are, by definition, supposed to be pills, powders, concentrated liquids, capsules, things like that. By their very nature, they're not allowed to be presented as a food substitute. And so the very act of taking a supplement becomes very intentional."
He continues: "The problem they have with food is they're concerned about the cumulative effects of CBD if it's in everything-you know, you get up in the morning and you have a CBD-infused coffee, and then you have a CBD-laced bottle of water on your way to work, and then you have a CBD-infused brownie. Pretty soon, without realizing it, you're starting to get an awful lot of CBD into your system. That's, I think, what's problematic about food. It's very hard to do this in a way with food that you alert people to the potential dangers of overconsumption, and it's also hard to warn vulnerable populations away from it. If you don't want pregnant women using CBD, are they going to think about that when they're at the grocery store and they pick up cookies or coffee that has CBD in it? Whereas with a supplement, you can label that supplement in such a way that cautions people: Do not use this product if you're pregnant or nursing."
It's further important to note that if a bill like Rep. Peterson's passes and makes CBD a legal dietary ingredient, CBD would be subject to all of the regulations and enforcement that all other legal dietary ingredients face-for instance, adhering to the new dietary ingredient (NDI) process and safety data requirements, the current good manufacturing practices (cGMPs) law, as well as labeling compliance.
"Oh, absolutely," says Mister. "And I think that's something that some people don't understand, because they think that somehow it's exempting CBD from all of the regulatory framework, and that could not be more wrong. What it does is it simply says it meets the definition of a dietary ingredient, but before anybody can bring anything to market, it would still require that you meet all of the requirements for a dietary supplement…So it's not like a CBD supplement is going to get a free pass under this legislation, but what it does is it says, 'This is the swim lane for CBD.'"
Short of passage of the Peterson bill, could FDA take more action on sorting out CBD's legality in 2020? "It's hard to say," says AGG's Durkin. "I know that the agency never wanted to be put in this situation where this is dragged out for so long. I think an answer on CBD is long overdue, whether it comes from the agency in the form of regulations, or from the legislature in the form of a law. It's just hard to say when that's going to happen."
Although FDA has so far not changed its position on CBD's illegal supplement/food status, it is most definitely hearing all of the noise surrounding CBD. (In efforts to open communication, FDA hosted a public hearing last May to gather information on cannabis and cannabis-derived compounds.) Regarding enforcement, in 2019 the agency did issue more warning letters for violative CBD products it identified in the market. In 2019, it issued 22 warning letters, largely to blatantly violative companies, such as those making illegal disease claims.
FDA is facing a lot of pressure, not only from the new directives it faces from the 2020 spending bill, but more importantly from stakeholders and lawmakers to find a fix due to the mess that's growing around CBD-everything from companies selling questionable and potentially harmful products without oversight, to growing class action lawsuits over CBD and also the patchwork of state laws that are emerging as states try to take matters into their own hands to protect their own. Meanwhile, the CBD playing field remains uneven and unfair, as companies still cautiously abiding by FDA's legal stance are keeping out of the market.
"I do think that what's happening in the larger marketplace is creating some real strong pressures on FDA to do something," Mister says. "So, you have hemp farmers who are now growing hemp and finding that there's not a market for their product, and so the price for hemp has dropped because there's just not the marketplace because people can't put it in supplements; they can't put it in food. You've got these class action litigations that are really now impacting the industry…You've got states-and I would not underestimate the impact that is having-a number of states are jumping into this vacuum and saying, 'Well, we'll fill the void if FDA's not going to do anything.' Some states are making it completely illegal; many other states are saying, 'We're going to allow CBD in our state, but we're going to put various kinds of restrictions or requirements on it.' So you have one state that says you have to have a QR code on the label; another says you have to register your product with the state; another says we want certain warnings on the label. That's going to put increasing pressure on FDA, because think about this: If they wait three years to do something, how are they ever going to roll back all of those state bills? You're going to have this crazy patchwork in addition to whatever FDA does. So, I think all these things are putting very strong pressure on Congress and FDA to do something, and to do it now."
Of Rep. Peterson's bill, says AGG's Bell, "if you can help try to lead or influence a horse to water, and that horse is the FDA, this is a good way to do that." He adds that "really, the primary purpose to put it out there was more to spread the idea of a recommendation and potentially, hopefully, influence [FDA] by virtue of it coming from a member of Congress, or several members of Congress…"
How should companies proceed in these uncertain times? Beyond the possibility of receiving FDA warning letters, Mister advises, CBD companies should be even more concerned about ramped-up enforcement that could come from the FTC over fraud and misleading advertising. Already, the FTC has indicated that it is beginning to investigate CBD firms, and those FTC cases "will involve significant settlements of money," Mister says, and have "a lot more teeth than a warning letter. So that would be my bigger concern."
And, says AGG's Durkin, FDA could further enforce against CBD companies through the cGMP process. "I think the agency's priorities will remain committing their limited resources towards products that are making disease claims. After that, I think if products labeled to contain CBD are found during a routine [cGMP] inspection, I think we can expect the agency to insist that those products be removed from commerce or destroyed before they close that inspection. They're not gonna walk away from that anymore-not that I would say they ever have-but I don't think they're going to miss the opportunity to enforce the Act when they find this violation through day-to-day business."
We asked a few well-known supplement companies selling CBD or hemp extract products what advice they would give other CBD companies on how to try to stay out of trouble with FDA. Their advice mirrors advice one would give about any other kind of dietary supplement product.
"If you're selling CBD, there's no surefire way to avoid landing in hot water with the FDA, since their position is that it is not currently lawful to sell CBD products as dietary supplements," says Gene Bruno, MS, MHS, RH(AHG), senior director of product innovation for Twinlab. "That being said, it is also clear that they haven't take measures to shut down the sales of all such products currently on the market..." His top advice to companies includes avoid making "outrageous, red-flag" disease-treatment claims; avoid using CBD isolates, "since indications are that when all is said and done, this material will be exclusively available to GW Pharmaceuticals as the major component of their prescription drug, Epidiolex;" and "If you really want to reduce risk, offer hemp extract products, not CBD products."
Stuart Tomc, vice president of human nutrition, CV Sciences (San Diego, CA), adds: "Companies should be following all of the applicable rules that are in place to protect consumers, For example, if a company is selling a dietary supplement, then the company's marketing surrounding the supplement should follow all dietary supplement rules. Those rules include having evidence that the level of CBD in their product is safe. The company's marketing messaging for the product should not make any unsubstantiated claims, the product should be made in a cGMP facility, and the company should be collecting and monitoring consumer complaints or adverse events."
The biggest fear of all, for all involved-FDA, lawmakers, responsible CBD companies-is what were to happen if a consumer were to become ill or injured from a CBD product for reasons including that it was misbranded, adulterated, or otherwise dangerous.
"First and foremost is public health," says Daniel Fabricant, PhD, CEO and president of the Natural Products Association (NPA; Washington, DC). Fabricant has been vocal in urging FDA to determine a safe CBD usage level for consumers, also keeping in mind that CBD users today could include children or pregnant women.
"The CBD being sold in stores and online is made up of who-knows-what and comes from who-knows-where. If the FDA, on their own, or as mandated by Congress, doesn't act soon to set a safe level of consumption for CBD, then we are inviting another vaping-like crisis or worse."
He adds that he's "not sure of the delay by the agency to set even an interim level…[T]here's so much in the public domain, like the WHO document on CBD, that could be easily used as a starting point."
Short of regulatory clarity, expect the CBD market to continue the same extraordinary growth it saw in 2019 and even ramping up to last year. The journal HerbalGram, published by the American Botanical Council (Austin, TX), reported2 that by the end of 2018, CBD had skyrocketed to the top as the number-one top-selling herbal supplement in the U.S. natural channel, effectively pushing turmeric, the previous number-one natural seller since 2013, down to the number-two spot. CBD was the top-selling and the fastest-growing natural-channel ingredient that year, with sales reaching nearly $53 million and growing 332.8% from the previous year. The HerbalGram report stated: "According to SPINS, roughly 60% of the CBD products sold in the U.S. natural channel in 2018 were in the form of alcohol-free tinctures, followed by capsules and softgels. The vast majority of the CBD products were marketed for 'non-specific health focuses,' with mood support and sleep as the next most-popular uses."
2019 saw the same impressive growth for CBD in the U.S. natural channel, according to data provided by SPINS for this story. In the U.S. natural channel in 2019, CBD ranked as the number-two bestselling ingredient, growing 113% to $90 million in sales. (For more insights on CBD's cross-channel growth in 2019, read our article, 2019's Biggest ingredient sales trends (positive and negative) for dietary supplements.)
That growth looks set to continue, other developments notwithstanding. At last November's Council for Responsible Nutrition The Conference, market researcher and presenter IRI (Chicago) predicted that U.S. market sales of non-THC cannabinoids, including CBD, could reach $18 billion by 2024, including sales in the general retail supplement channel and in dispensaries-and not even capturing data from other retail outlets not tracked where CBD might be sold, such as in household stores or other types of retail stores-and largely driven not only by wider consumer acceptance of CBD but also growing availability.
During his presentation, IRI's Robert Sanders, executive vice president, healthcare and nutritional supplement practice leader, also pointed out that "a leading indicator for what's going to happen in the [mainstream] marketplace…will be driven in a large way by what's going on in dispensaries. So if dispensaries are doing things, you can expect that to be a rationale for other retail channels that want to do the same thing." He also said that dispensaries' share of the market will shrink as market share held by other retail outlets, including mass-market and grocery stores, grows. And, while CBD supplements are driving most of the CBD sales in traditional retail outlets, moving forward, much of CBD's growth will stem from edibles (food, candy, drinks) and topicals (beauty/skin products).
Already, CBD is being sold in mainstream national stores like CVS, Walgreens, Rite-Aid, Kroger, GNC, Ulta Beauty, Sephora, Bed Bath & Beyond, and clothing stores. Says CV Sciences' Tomc, "Retailers are gaining confidence that CBD derived from agricultural hemp is here to stay," although he adds that "conservative retailers…are standing on the sidelines."
For the time being, many large CPG players will be waiting to engage until FDA makes CBD products legal. "I think the temptation may be too much for a few players, and they will get in, but I think most of your large CPG companies are just not going to wade into this area as long as there is uncertainty about whether it's a legal product," CRN's Mister says.
He adds: "And that's really unfortunate, because if you were to ask FDA, 'What's the kind of company you would like to see in this space?,' they would like to see big established companies that have very well-developed quality-control systems in place, that have a commitment to their consumers, and that are too big to get wrapped up in a lot of lawsuits. Those are the kinds of companies that are going to do it right, and instead, those are the ones that are sitting on the sidelines in many cases….And that's exactly the kind of company that FDA would rather come in and take market share."
And, indeed, the CBD market today is largely populated by smaller companies-including some new-to-business companies with little knowledge of dietary supplement best manufacturing practices or supplement regulation requirements.
"New brands have continued to enter the marketplace, typically with small companies not previously affiliated with the dietary supplement industry," says Twinlab's Bruno. "That's not to say that existing supplement companies haven't introduced CBD/hemp products-they have. It's just that the sheer number of new brands are from the smaller companies."
CV Sciences' Tomc echoes this. "The dietary supplement market has been flooded with start-ups and new CBD brands that have migrated to the dietary supplement category. These companies are not familiar with dietary supplement regulations that are currently in place to protect consumers. Therefore, the market has been flooded with non-compliant products with claims that may not be allowed, or claims that may fail to meet specifications when tested."
Opportunities are ripe for irresponsible CBD companies coming to market to make a quick profit with questionable products-and, in the process, risking the reputation of both the CBD market and the larger supplement market as a whole. An NPA poll conducted last year found that 47% of Americans would stop using CBD products if they or someone they knew got sick from using CBD, Fabricant points out.
"My biggest concern about the CBD supplements industry is irresponsible players," Bruno says. "Unfortunately, many new brands to the industry aren't necessarily planning on a long-term commitment and so are less concerned with following cGMPs, and more concerned with maximizing profits to the exclusion of all else…When I was at SupplySide West in 2019, I met someone with a brand who had illegal levels of THC in his product and was happy about it, since he figured it would get customers to keep buying the products.'"
AGG's Bell says, "The last few years when I've gone to SupplySide West and people come up and ask me questions about cannabis and CBD…you know, at some point in time, you look at what it's starting to populate, these trade shows and conferences, and say, '90% of you people probably won't make it. You won't be here.' You try to figure out how much of this is a quick buck versus the ones who are really serious about this."
It's a major concern for any CBD company doing its best to act responsibly. Says CV Sciences' Tomc, "The biggest concern is the risk for consumers to be harmed by a poorly made product. This gives responsible industry a black eye at a time when the industry is working hard to provide FDA with the science needed to establish that there are, indeed, high-quality hemp-derived CBD products that are safe when used correctly."
Says AGG's Durkin: "There are some very good players making products that contain CBD, and although they're violating the Act by doing that, they go through great efforts to make sure that they're adhering to all other aspects of the Act in that they're putting a quality product on the market. I don't want to see those good players suffer because someone doesn't put the same effort in and puts a product out there that causes harm."
For better or for worse, Bruno also points out that for newer companies trying to enter the CBD market now, eventual market saturation will become an issue. "At this point in time, any new CBD brand wishing to enter the retail will likely have a hard time doing so. There are already more than 1500 such products, and unless you can differentiate your product in a major way, it won't really be worth the effort to try and be a player. In my opinion, one viable approach is for a new CBD brand to focus on products that provide other cannabinoids besides just CBD."
2020 Ingredient Trends to Watch for Food, Drinks, and Dietary Supplements:
ElderberryMelatoninMCTsMagnesiumAshwagandhaCollagenDietary Fiber/Prebiotics
Dimengo N. "The 12 Weirdest CBD Products." GreenEntrepreneur. Published November 1, 2019. Accessed at: www.greenentrepreneur.com/slideshow/341602
Smith T. "Herbal supplement sales in US increase by 9.4% in 2018." HerbalGram, no. 123 (2019). Accessed at: http://cms.herbalgram.org/herbalgram/issue123/files/HG123-HMR.pdf
Download Issue : Nutritional Outlook Vol. 23 No. 1
Trends & Business | Food & Beverage | Herbs & Botanicals | Regulatory


This Deluxe Care Kit contains 6 Facial Wipe Packs (30 wipes in each), 1 Dozen (12) Mascara Wands, and Protective Goggles for the Shower along with a Beyond Beauty Lashes carry bag.
Treat your face to the Aloe Vera makeup cleansing tissues. These facial tissues will deep clean without irritating your skin.


Advance your expertise in security architecture.
Go beyond the CISSP and challenge yourself in the field of information security architecture. When you earn the CISSP-ISSAP, you will demonstrate competency in designing security solutions and providing management with risk-based guidance to meet organizational goals.
The Ultimate Guide to the CISSP-ISSAP is a must-have resource if you are planning to sit for the exam – and it was developed by (ISC)², the creator of the CISSP-ISSAP Common Body of Knowledge (CBK).


text:
Hanging Around … LA's Adam West tribute
Hundreds of fans gathered at the steps of Los Angeles City Hall last night to pay tribute to Adam West, the actor best known for playing Batman in the 1960s TV show. West died Saturday after a short battle with leukemia.
The ceremony was brief, but heartfelt. Los Angeles mayor Eric Garcetti, LAPD Chief Charlie Beck and West's costar Burt Ward all shared what he meant to them. West's family, his co-star Lee Meriwether and co-publisher of DC Entertainment Jim Lee were also in attendance and a Bat Phone and Batmobile from the show were on display.
The event culminated with the iconic Bat Signal being projected onto the front of City Hall.
Photos and article by Joel Murphy.
Hobo Radio 599 - From the beautiful twisted minds of Joel and Lars
Hobo Radio 595 - If you're ever in doubt, listen to Gail Simone
Hobo Radio 592 - Heroes don't do that
Silver Linings Playback 47 - Watchmen
Hobo Radio 580 - Marvin Thanos
Batman's Happy Days

redpajama_set_name: RedPajamaCommonCrawl


With the completion of the new Narrows Road bypass, the town received more than just a road — it received a parking lot, big enough for roughly 100 vehicles, located in the midst of four baseball fields.
Selectwoman Jean Fox said after an initial disagreement with the Federal Emergency Management Agency, the parking lot will be paid for mostly through FEMA funds as part of the Narrows Road bypass, which opened at the end of last year.
The bypass road was built to allow authorities to fix the Narrows Road Bridge, which sustained damage during the floods of March 2010.
Interim Town Administrator John Healey said the parking lot, adjacent to the bypass road, will be paid for as part of the FEMA-approved $511,000 bypass project.
He said FEMA will pay for 75 percent of the costs, or $383,000.
Fox said the town went ahead and paved a parking lot for safety reasons — even before FEMA approved it.
Freetown Youth Athletic Association President Kevin Richard recently said the presence of the bypass road near the ball fields has posed safety concerns. He approached Fox about the town placing portable speed bumps on the bypass route.
Safety authorities last month said the speed bumps were unnecessary because the road's many curves make it difficult for motorists to generate significant speed.
Police Lt. Charles Sullivan added many motorists might drive around the speed bumps.
Fox, who is still in favor of installing speed bumps, acknowledged the area is frequented by youngsters.


UK Documentary Exposes Islamism in UK Mosque – The Tundra Tabloids…….
A UK Channel 4 documentary uses taped video and audio material by an undercover reporter to document what kind of messages are being preached inside a British Mosque.
The Kuffar (infidel/non-Muslim) should be hated, women are "deficient", kids should be beaten, non-Muslim are not to be trusted because all are liars, an Islamic state is the main goal of all Muslims regardless of the democracy in which they live, the practice of marrying pre-pubescent girls is allowed by the Prophet and should not be discouraged.
I am reminded of an exchange I had with the blogger Toby over at Northern Lights blog, over the subject of women/girls wearing the hijab. It was during the time when former UK Foreign Minister, Jack Straw, commented that he would like to see the face of all his patients inside his surgery. Which I happen to think is a rather fair request. In part two of the documentary, the clerics bring up the subject of beating females into wearing them, which was the exact same point I made to Toby.
Once more, the phenomenon of taking at face value the words of people who live within a violent environment is at issue. I contend that they (the victimized) are as free to express their opinions, as was a black man on the streets of Alabama during segregation, or like a beaten house wife or an abused child. The victimized will more than likely side with their tormentor, (when outsiders intrude) which only serves to prolong their vicimization as well as obfuscate their prediciment to those on the outside looking in.
Previous Post Previous Post Moonbat Pali Protesters Play Pocohantos…….
Next Post Next Post Good News For a Change From The ME…….


his name was Bill. Few would have thought that this scruffy little rancher's son would grow up to be a smart, confident, well spoken young gentleman. Nobody would have thought that he would grow up to head up one of the biggest missions that America, or the world had ever known. Campus Crusade was just the beginning though. Soon there were missions to students, the military, athletes and Hollywood actors – and then Bill was involved in making a film himself – a film about the one he loved above all else – Jesus.
Bill Bright: Dare to be Different by Kim Twitchell was published by Christian Focus Publications in June 2004 and is our 28879th best seller. The ISBN for Bill Bright: Dare to be Different is 9781857929454.
Be the first to review Bill Bright: Dare to be Different!
Got a question? No problem! Just click here to ask us about Bill Bright: Dare to be Different.


text:
\section{Introduction}

Tracking multiple objects in video is critical for many applications, ranging from vision-based surveillance to autonomous driving. A popular solution to Multiple Object Tracking (MOT) is the tracking-by-detection strategy, in which, detections from an external detector on each frame are associated and connected to form target trajectories in either online or offline batch mode. With recent progress on object detector, tracking-by-detection has been successful in multiple domains~\cite{leal2014learning,bae2014robust,lenz2015followme,milan2016multi,wu2012coupling,brendel2011multiobject,berclaz2011multiple,leibe2007coupled,jiang2007linear}. However, separation of detection from tracking keeps detector inaccessible to the frame-to-frame correlation information which identifies the difference between object detection in still images and in videos. Moreover, the dependence on detection becomes a major limitation in complex scenes due to the degraded detection reliability caused by large size variation and partial occlusion of targets.

MOT, on the other hand, can be viewed as a generalized Single Object Tracking (SOT) problem where target locations are estimated from multiple SOT tracking models. Significant improvement has been achieved in recent SOT approaches which are efficient and robust in complex scenes~\cite{henriques2015high,li2014scale,bertinetto2016staple,fan2017sanet,fan2017parallel}. However, even with a proper target management mechanism, directly applying multiple SOT trackers simultaneously to track multiple targets still experiences various difficulties.

A SOT tracker usually allows certain generalisability to capture appearance changes of target. In the MOT context, however, multiple similar targets may appear in the searching area of a SOT tracker. Such targets from the same category (e.g., pedestrian) often share similar appearance or shape that may confuse traditional SOT trackers. When this happens, SOT trackers for multiple targets may easily drift and even end up tracking the same target. Moreover, since SOT trackers depend heavily on the model learned at the first frame, steady tracking of a model-free SOT tracker requires groundtruth bounding box of target at the first frame to correctly distinguish the target from its background. In the current MOT framework, all target candidates are provided by a real detector which usually yields considerable noise in both target location and scale.

In this work, we propose using \emph{instance-aware} (IA) tracker to both harvest the merit of SOT techniques and address the above issues in MOT. In addition to distinguishing a target from background as ordinary SOT tracker, our IA tracker tracks with the awareness of all other instances and their tracking models, which often means different targets of the same category. We implement such awareness in both target and global level. In scope of each target, we formulate the IA tracker in the efficient kernel correlation filter framework, while fusing features that tell a target from both background and other instances. This way, an IA target model is entitled with the awareness of differences between instances thus enhances response to its own target while suppressing responses to other similar targets. In global scope, generated response maps for all target models are used integrally to predict the target locations for a new coming frame. Awareness between targets models is treated as an optimization problem to maximize the overall response that each target is tracked exclusively by only one target model. A detection verification mechanism is proposed to solve the global optimization problem efficiently by incorporating detections from detectors and predictions from target models. And instead of updating model gradually, identity of a target model in proposed method is reinforced through a model refreshing mechanism, which is adaptively learned via a convolutional neural network.

Our contributions are mainly two-fold:
\begin{itemize}
\item We propose a novel instance-aware tracker to effectively integrate SOT in MOT. By being instance-aware inherently and mutually, target models significantly improve their capability to solve the ambiguity of similar targets in neighborhood.

\item We propose an adaptive model refreshment strategy to further improve the reliability of SOT in MOT context.
\end{itemize}
To show the effectiveness of the proposed approach, it is evaluated on the popular MOT15 and MOT16 challenge benchmarks. On both benchmarks, our approach achieves the best overall performances in comparison with published results.

\section{Related Work}
\label{sec_relate_work}
Recent works on MOT primarily focuses on the tracking-by-detection principle. Most of these methods can be roughly categorized into two groups. The first group treat MOT as an offline global optimization problem that uses frame observation from both previous and future to estimate the current status of targets~\cite{ban2016tracking,pirsiavash2011globally,kim2016cdt,manen2016leveraging,mclaughlin2015enhancing}. These methods usually focus on data association based methods such as Hungarian algorithm~\cite{bewley2016simple,huang2008robust}, network flow~\cite{zamir2012gmcp,zhang2008global} and multiple hypotheses tracking~\cite{kim2015multiple}. Their performance heavily depends on the quality of detections from external detector. Different from these methods, our approach learns tracking model for each target to search and predict locations of next frame online. Detections in our approach are only used for model uniqueness verification and model refreshing.

The second group only needs observations till to the current frame to online estimate target status~\cite{yang2012online,fagot2015online,xiang2015learning,sadeghian2017tracking,chu2017online,yan2012track,yoon2015bayesian}. In \cite{xiang2015learning}, MOT is formulated as a Markov decision process with a policy estimated on the labeled training data. \cite{sadeghian2017tracking} extends the work \cite{xiang2015learning} to use deep CNN and LSTM to encode long-term temporal dependencies by fusing clues from motion, interaction and person re-identification model. Chu, et al.~\cite{chu2017online} use a dynamic CNN-based framework with a learned spatial-temporal attention map to handle occlusion, where CNN trained on ImageNet is used for pedestrian feature extraction. Yan et al.~\cite{yan2012track} gather target candidates from both detector and independent SOT trackers and select the optimal candidates through an ensemble model. Our approach differs from these methods by adding awareness between SOT trackers and dynamically refreshing model to eliminate possible noise in model initialization.

\section{System Overview}
\label{sec_overview}
For the $t$-th frame, our tracking system takes image frame and detections from an external detector as input, as shown in Fig.~\ref{fig:system_overview}. Target models of instance-aware tracker are used to predict target locations independently and estimate scores for each detection. A detection verification process is applied to assign each spatial candidate exclusively to only one tracked target and verify the uniqueness of their target model as detailed in Sec.~\ref{sec:tekcf} and  Sec.~\ref{det_verif}. Model of verified target will be refreshed if assigned detection enclosing target better than its model prediction. Unverified targets and detections will be matched again using backup models to recover from incorrect refreshment. These components are explained in Sec.~\ref{model_refresh}. Further, unpaired predictions and detections are passed into occlusion handling. Final unverified targets will exit when they have not been verified for some continuous frames. Unpaired detections will be added as new targets as described in Sec.~\ref{targ_m}.

\section{Methodology}
\label{sec_method}
\subsection{Problem Formulation}

Following the tracking-by-detection paradigm, online MOT can be formulated as an optimization problem, at frame $t$, the set of $N^t$ target locations $\hat{\bm{X}}^{t} = \big\{ \hat{x}^{t}_{i}\big\}^{N^t}_{i=1} $ in current image $I^t$ are chosen from $M^t$ candidates in set $\bm{O}^t = \big\{x^{t}_j\big\}^{M^t}_{j=1}$ to maximize a score:

\begin{equation}
\hat{\bm{X}}^{t} = \argmax_{\bm{X}^t \subset \bm{O}^t} f(I^t, \bm{X}^t; \mathbf{a}^{t}, \bm{W}^{t-1}).
\end{equation}
\begin{equation}
\text{s.t.} \quad \sum_i a^{t}_{ij} \le 1, a^{t}_{ij} \in \{0, 1\}.
\label{eqn:st}
\end{equation}
The parameter $\mathbf{a}^{t} = \big\{a^{t}_{ij}\in\{0,1\}\big\}$ indicates the association between the $i$-th tracked targets in $\hat{\bm{X}}^{t - 1}$ at frame $t - 1$ and the $j$-th candidate location in $\bm{X}^{t} $ at frame $t$. $a^{t}_{ij} = 1$ if $\hat{x}^{t - 1}_{i}$ is associated with $x^{t}_{j}$, and $a^{t}_{ij} = 0$ otherwise. Each candidate can only be assigned to at most one tracked target. $\bm{W}^{t} = \big\{\mathbf{w}^{t}_i\big\}^{N^t}_{i=1}$ is the set of parameters to model each target, which is usually learned through a training procedure using the appearance or location information of target.

The objective function $f(\cdot)$ measures the overall quality of the tracking results for all targets at frame $t$, defined as below
\begin{equation}
\label{f}
f(I^t, \bm{X}^t) = \sum_{ij} a^{t}_{ij} g_i(I^t, x^{t}_j; \mathbf{w}^{t - 1}_i).
\end{equation}
The set of functions $g_i(.)$ can be interpreted as the objective function for tracking single target such that $ g_i(I^t, x^{t}_j; \mathbf{w}^{t - 1}_i)$ assigns a score to the $j$-th candidate location $x^{t}_j$ on $I^t$ according to the $i$-th model parameter $ \mathbf{w}^{t - 1}_i \in \bm{W}^{t-1}$. The model parameters should be determined by previous images and target locations up to frame $t-1$ .

Solving the online MOT problem, therefore, is to solve $\mathbf{a}^{t}$ and $g_i(.)$ for each frame.

\subsection{Instance-Aware Tracker}
\label{sec:tekcf}

\begin{figure}[!t]
	\centering
	\includegraphics[width=0.996\linewidth]{fig/fig2.pdf}
	\caption{Illustration of target level instance-awareness: discriminate targets from background and discriminate different targets. $\mathbf{z}_{\mathrm{det}}$ and $\mathbf{z}_{\mathrm{id}}$ are feature maps visualized by accumulating values in all channels. }
	\label{fig:feat}
\end{figure}

\begin{figure*}[!t]
	\centering
	\includegraphics[width=0.87\linewidth]{fig/fig3.pdf}
	\caption{Tracking multiple objects by instance-aware tracker with model refreshment.}
	\label{fig:tracking}
\end{figure*}

We propose to use Instance-Aware (IA) tracker to solve $\mathbf{a}^{t}$ and $g_i(.)$ in two levels. For each single target, objective function $g_i(I^t, x^{t}_j)$ is learned to only assign a high score to its own target while returns low scores for both background and other instances. As for global, $\mathbf{a}^{t}$ is solved to associate each spatial location $x^{t}_j$ on $I^t$ exclusively to only one target referring those scores from all targets.

We start from the objective function $g_i(I^t, x^{t}_j)$. Ordinary SOT methods focus on distinguishing target from background and allow certain variations to handle appearance change of target, which makes tracker insensitive to distracters that are apparently similar to target. Thus, directly adopting SOT methods for MOT causes the trackers easily drifting to wrong targets. In this work, we treat the problem of tracking single target in MOT context as two sub-problems: i) to distinguish targets from background; and ii) to model the difference between targets. The objective function can be rewritten as
\begin{equation}
g_i(I^t, x^{t}_j) = g_{\mathrm{det}}(I^t, x^{t}_j; \bm{\theta}^{t-1}_i) + g_{\mathrm{id}}(I^t, x^{t}_j; \bm{\epsilon}^{t-1}_i),
\label{eqn:single_obj}
\end{equation}
where $\bm{\theta}^{t-1}_i$ and $\bm{\epsilon}^{t-1}_i$ are the two model parameters for the $i$-th target focusing on each of the problems mentioned above, therefore $ g_{\mathrm{det}}(I^t, x^{t}_j; \bm{\theta}^{t-1}_i)$ estimates the score for location $x^{t}_j$ containing one of the targets using model parameter $\bm{\theta}^{t-1}_i$, $g_{\mathrm{id}}(I^t, x^{t}_j; \bm{\epsilon}^{t-1}_i)$ evaluates the similarity for object at $x^{t}_j$ referring to the $i$-th target using model $\bm{\epsilon}^{t-1}_i$. Benefit of the separation is that for some target categories each of the sub-problems already has well-founded methods and datasets for model learning. For example, in the case of tracking multiple pedestrian, the first sub-problem is pedestrian detection and the second one is person re-identification, and both have large scale datasets such as MSCOCO, CUHK~\cite{li2014deepreid}.

We focus on the Ridge Regression form of $g_{\mathrm{det}}(.)$ and $g_{\mathrm{id}}(.)$, in which, the functions share the form of $g(\mathbf{z};\mathbf{\Phi}) = \mathbf{\Phi}\mathbf{z}^T$ with $\mathbf{z}$ for regression input and $\mathbf{\Phi}$ for learnable parameter. Then the objective function in Eq.~\ref{eqn:single_obj} can be rewritten as
\begin{equation}
\begin{split}
g_i(I^t, x^{t}_j) &= \bm{\theta}^{t-1}_i \bm{T}_{\mathrm{det}}(I^t, x^{t}_j)^T + \bm{\epsilon}^{t-1}_i \bm{T}_{\mathrm{id}}(I^t, x^{t}_j)^T \\
&= \mathbf{\Phi}^{t - 1}_i \Big[\bm{T}_{\mathrm{det}}(I^t, x^{t}_j), \bm{T}_{\mathrm{id}}(I^t, x^{t}_j) \Big]^T
\end{split}
\end{equation}
where $\bm{T}_{\mathrm{det}}(., x^{t}_j)$ and $\bm{T}_{\mathrm{id}}(., x^{t}_j)$ are image transformations centering at $x^{t}_j$, $[.]$ is channel-wise concatenation, $\mathbf{\Phi}^{t - 1}_i$ is the combined model parameter for the $i$-th target. An illustration is shown in Fig.~\ref{fig:feat}.

Solving $\mathbf{\Phi}^{t - 1}_i$ online usually involves carefully designed strategies for positive and negative sample collection. Kernel Correlation Filter (KCF) tracker proposed in \cite{henriques2015high} solve this problem efficiently in Fourier domain by combining circulant matrices and kernel trick. Following this formulation, model parameter of the $i$-th target at frame $t$ is obtained by $ \mathbf{\tilde{w'}}^{t}_i =  \frac{\mathbf{\tilde{y}}}{ \mathbf{\tilde{k}}^{\mathbf{z}^t\mathbf{z}^t} + \lambda}$,
where $\mathbf{z}_{t} = \Big[\bm{T}_{\mathrm{det}}(I^t),\bm{T}_{\mathrm{id}}(I^t) \Big]$ is the feature map, $\mathbf{k}^{\mathbf{z}^t\mathbf{z}^t}$ is defined as kernel correlation in \cite{henriques2015high}, $ \mathbf{\tilde{y}}=\mathcal{F}(\mathbf{y})$ is Discrete Fourier Transform (DFT) of regression labels. If considering a SOT context where only one target presents, an predicted location  $^{P}\!\hat{{x}}^{t}_{i}$ using the $i$-th target model then can be estimated as
\begin{equation}
\label{prediction}
^{P}\!\hat{{x}}^{t}_{i} = \argmax_{x^{t}_j \in \bm{O}^t} \mathcal{F}^{-1}(\mathbf{\tilde{k}}^{\mathbf{z}^{t-1}\mathbf{z}^t} \odot \mathbf{\tilde{w}}^{t - 1}_i)  \bigr\vert_{=x^{t}_j}.
\end{equation}

Now we apply the objective function of tracking a single target to MOT context by combining Eq.~\ref{f} and Eq.~\ref{prediction}. Given the set of $\big\{x^{t}_j\big\}$, the objective function of IA tracker subject to constrain in Eq.~\ref{eqn:st} is defined as
\begin{equation}
f(I^t, \bm{X}^t)=\max_{a_{ij} } \sum_{ij} a^{t}_{ij} \mathcal{F}^{-1}(\mathbf{\tilde{k}}^{\mathbf{z}^{t-1}\mathbf{z}^t} \odot \mathbf{\tilde{w}}^{t - 1}_i)  \bigr\vert_{=x^{t}_j}
\label{eqn:graph_org}
\end{equation}

The core idea of IA tracker can be explained as follow. In SOT version of KCF tracker, prediction is the spatial location strongest responding on response map given by  $\mathcal{F}^{-1}(\mathbf{\tilde{k}}^{\mathbf{z}^{t-1}\mathbf{z}^t} \odot \mathbf{\tilde{w}}^{t - 1}_i)$. While in MOT, each spatial location has multiple responses generated by different  target models of frame $t-1$ as shown in Fig.~\ref{fig:tracking}. And to further confirm each target is tracked exclusively by only one target model, we make use of the spatial exclusive assumption that no two or more targets can occupy the same position on image at the same time (on image frame only, not considering real 3D space). Thus, a global optimization in Eq.~\ref{eqn:graph_org} is employed to maximize the overall response subject to the spatial exclusive constrain defined in Eq.~\ref{eqn:st} that each spatial location on image belongs to at most one target.
Notice that, in calculation, $\mathbf{z}^{t}$ usually covers the search area of a target model only, where it should be written as $\mathbf{z}^{t}_i$ and the actual coordinate of $x^{t}_j$ in $\mathbf{z}^{t}_i$ should also be converted accordingly.

\subsection{Detection Verification}
\label{det_verif}

Solving the optimization problem in Eq.~\ref{eqn:graph_org} for all spatial locations on image frame, e.g. each pixel, is computationally impractical. Ideally, a subset whose elements are complete and spatial exclusive is preferred. Prediction $^{P}\!{x}^{t}_{j} \in \bm{P}^t$ from Eq.~\ref{prediction} contains all possible locations for all targets, but these locations may have potential spatial conflicts. Detections $^{D}\!{x}^{t}_{j} \in \bm{D}^t$ from a category detector are spatial exclusive but not complete due to the possible false negative. We use the combination of detection $^{D}\!{x}^{t}_{j} \in \textbf{D}^t$ and predictions $^{P}\!{x}^{t}_{j} \in \textbf{P}^t$ as the candidate locations set $\bm{O}^t = \bm{D}^t \cup \bm{P}^t.$ Result candidate set is complete but only partially spatial exclusive.  Therefore, we propose a detection verification mechanism to solve $\mathbf{a}^{t}$ for all targets leveraging the limited spatial exclusive information provided by $\bm{D}^t$.

If a graph $G(\bm{V}, \bm{E})$ is created on $\bm{V} = \hat{\bm{X}}^{t - 1} \cup \bm{O}^t$ and $\bm{E}$ which are the edges between vertexes in $\bm{V}$, the optimization problem in Eq.~\ref{eqn:graph_org} with constrain in Eq.~\ref{eqn:st} can be reformed as a graph multicut problem minimizing cost:

\begin{equation}
\min_{c_{e} \in \{0, 1\}} \sum_{e \in E} c_{e} d_{e}
\label{eqn:graph}
\end{equation}
\begin{equation}
\text{s.t.} \quad \forall P_{uv} \in \mathcal{P} \quad \forall e \in P_{uv} : c_e \le \sum_{e' \in P_{e} \slash \{ e \}} c_{e'},
\label{eqn:graph_st}
\end{equation}
where $u,v \in \bm{V}$, $c_e$ is the binary label indicating if $e \in \bm{E}$ is a cutting edge, $d_e$ is the cost/reward associated to edge $e$, $P_{uv}$ is the set of path from $u$ to $v$, $e$ is the edge between $u$ and $v$. Solving Eq.~\ref{eqn:graph} and Eq.~\ref{eqn:graph_st} in the context of MOT is to find the subgraphs, in which, candidate locations belonging to the same target are connected while belonging to different targets are separated by cutting edges as shown in Fig. \ref{fig:tracking}.

After optimization, each $^{D}\!{x}^{t}_{j}$ is assigned to one of the tracked target $ \hat{x}^{t - 1}_{i} \in \hat{\bm{X}}^{t - 1} $. Verification of each target tracked exclusively by only one tracking models can be done by checking whether a tracked target assigned with detections. Due to the possible false negative and false positive generated by a real detector, verification can only be conducted every $T_V$ frames to confirm the uniqueness of target model in long-term. Particular, if a tracked target has not been assigned with any detection for continuous $T_V$ frames, then its target model is likely tracking either a false positive target or a target shared with other models. Increasing $T_V$, therefore, decreases awareness between target models since it allows each target model to track independently for more frames. $T_V$ also controls the dependency on external detection and can be adjusted to adapt different detection qualities. Detailed parameter choice and discuss for $T_V$ are described in Sec.~\ref{sec_tv}.

We employ a primal heuristic based approach proposed in \cite{keuper2015efficient} for solving Eq.~\ref{eqn:graph} with Eq.~\ref{eqn:graph_st}, where a set of transformation sequences are used to update the bi-partitions of a subgraph. Specifically, cost of each edge in Eq.~\ref{eqn:graph} is calculated as:
\begin{equation}
d_{e} \doteq d_{uv} = \begin{cases}
g_{i}(I^t, x^{t}_j), &\mathrm{if~} u \in \hat{\bm{X}}^{t - 1}, v \in \bm{O}^t \\
\mathrm{IoU}(\bm{b}^{t}_j, \bm{b}^{t}_{j'}) , &\mathrm{if~}  u \in \bm{O}^t, v \in \bm{O}^t \\
-C , &\mathrm{if~}  u \in \hat{\bm{X}}^{t - 1}, v \in \hat{\bm{X}}^{t - 1} \\
\end{cases}
\end{equation}
where $\mathrm{IoU}(.)$ calculates the bounding box overlap ratio in term of Intersection over Union, $\bm{b}^{t}_{j}$ is the bounding box associated with $x^{t}_j$, and $C$ is large positive constant to ensure cutting between different tracked targets. The final equivalence between $a_{ij}$ and $c_e$ is defined as following
\begin{equation}
a_{ij} = \begin{cases}
\bar{c}_e = \bar{c}_{uv}, & \mathrm{if~} u \in \hat{\bm{X}}^{t - 1}, v \in \bm{O}^t \\
0, & \mathrm{otherwise}
\end{cases}
\end{equation}
where $\bar{c}_e$ stands for the logical negation.

\begin{table*}[!h]
	\small
	\begin{center}
		\caption{Tracking Performance on the MOT training set.}
		\label{tab_tv}

		\begin{tabular}{cccccccccccc}
			\hline\hline
			\multicolumn{12}{c}{Venice-2}\\
			\hline
			$T_V$&0&1&2&3&4&5&6&7&8 &10 & 20 \\
			MOTA&27.0&30.9&32.7&33.7&34.4&32.4&33.1&33.4& 33.1 &  34.1 & 31.5\\
			FP & 647 &708 &773 &795 &824 &864 &889 &922 &942 &961   & 1237 \\
			FN& 4498 &4173 &3991 &3898 &3825 &3931 &3856 &3801 &3801 &3714    & 3622\\
			\hline
			\multicolumn{12}{c}{MOT16-05}\\
			\hline
			$T_V$&0&1&2&3&4&5&6&7&8 & 10 & 20\\
			MOTA& 39.5&40.3&40.9&41.1&41.2 &42.3&42.3&42.2& 40.9 & 40.0& 37.8\\
			FP & 187  &231 &255 &281 &312 &324 &340 &355 &415 & 492 & 693\\
			FN & 3522 &3441 &3387 &3349 &3314 &3240 &3228 &3216 &3241 & 3222&3152\\
			\hline\hline
		\end{tabular}

	\end{center}

\end{table*}

\begin{table*}[!h]
	\small
	\begin{center}
		\caption{Tracking Performance on the MOT training set}
		\label{tab:ab}
		\begin{tabular}{lcccccccc }
			\hline\hline
			Method & MOTA$\uparrow$ & MOTP$\uparrow$ & MT$\uparrow$ & ML$\downarrow$ & FP$\downarrow$ & FN$\downarrow$ & IDS$\downarrow$ & Frag$\downarrow$\\
			\hline
			IA & 26.1 & 69.3 & 15.4\% & 26.9\% &  991  & 4250 &  39  & 42 \\
			IA+MR & 33.3 & 74.0  & 15.4\% & 34.6\% & 785 & 3939 &  36 &  53\\
			IA$-$DV+MR & -35.3 &  72.7 & 38.5\% &  19.3\% & 6734 & 2856 &  70  & 108 \\
			IA$-$TA+MR & 32.2 &  73.7 & 15.4\% &  38.5\% & 760 & 4039 &  43  & 53 \\

			Full & 34.4 & 74.1& 15.4\% &  30.8\%  &824 &3825 &36& 66\\
			\hline\hline
		\end{tabular}

	\end{center}
\end{table*}

\subsection{Model Refresh}
\label{model_refresh}
We train a CNN based classifier to determine whether to refresh the tracking model of a target using its assigned detection. Target model in ordinary SOT methods is initialized by target groundtruth in the first frame and is slowly and constantly updated.  While in MOT, models are initially learned from detections which contain considerable noise in location and scale. And when targets moving close to the camera, their scale also will change rapidly. Due to those reasons, models in MOT have to be refreshed frequently.

Specifically, feature maps centering at tracked target $^{P}\!\hat{x}^{t}_{i}$ and its assigned detection $^D\!x^{t}_{j}$ are extracted and stacked channel-wise to feed into a CNN based classifier. The CNN is to make comparison between the bounding boxes associated with $^{P}\!\hat{x}^{t}_{i}$ and $^D\!x^{t}_{j}$ on target enclosing. If the bounding box of $^{D}\!x^{t}_{i}$ encloses target better, $\mathbf{w}^{t}_i$ will be refreshed by re-calculating $\mathbf{w}^{t}_i$ using $^{D}\!x^{t}_{i}$. In tracking phase, we reuse features from $\bm{T}_{\mathrm{det}}(I^t)$ and adopt ROI Pooing to exact feature maps at specific locations, as show in Fig.~\ref{fig:tracking}

We adopt reinforcement learning to train the CNN classifier for the model refreshing policy. We update the classifier or the policy only when it makes a mistake. Suppose the tracker is tracking the $i$-th target in $t$-th frame. There are two types of mistake that can happen. i) Bounding box of $^{D}\!x^{t}_{i}$ encloses target better than $^{P}\!\hat{x}^{t}_{i}$ referring to groundtruth bounding box, but classifier chooses not to refresh $\mathbf{w}^{t}_i$. Then features at $^{D}\!x^{t}_{i}$ and $^{P}\!\hat{x}^{t}_{i}$ are concatenated and added to training set as positive samples. ii) Bounding box of $^{P}\!\hat{x}^{t}_{i}$ encloses target better than $^{D}\!x^{t}_{i}$, but classifier chooses to refresh $\mathbf{w}^{t}_i$. Concatenated features in those cases are added as negative samples. Each time the classifier makes a mistake, the CNN is trained through a constant number of iterations using online batches of size $B_N$, which contains the newly added sample and $B_N - 1$ samples randomly sampled from the rest training set. We keep updating the policy until all the targets in training set are successfully tracked.

In case of classifier making mistake at real tracking phase, we adopt a model backup mechanism. In frame $t$, if classifier chooses to refresh $\mathbf{w}^{t - 1}_i$ with a new $\mathbf{w}^{t}_i$, $\mathbf{w}^{t - 1}_i$ will be saved. In frame $t + 1$, if tracker with $\mathbf{w}^{t}_i$ cannot be assigned with a $^D\!x^{t + 1}_{j}$, the old model $\mathbf{w}^{t - 1}_i$ will be restored for tracking and verification one more time.

\subsection{Target Management}
\label{targ_m}
In this work, except for `Tracked' event, we also handle the `Occlusion', `Enter' and `Exit' events of targets.

\noindent\textbf{Occlusion} To recovery a target from occlusion, we train an SVM classifier to estimate if two locations $\hat{x}^{t'}_{i}$ and $^D\!x^{t}_{j}$ are containing the same target. We make a simple assumption that a detection $^D\!x^{t}_{j}$ not assigned to any tracked target in detection verification and re-tracking phase is either a new target or an existing target just finished occlusion. Occlusion recovery thus is to connect that detection with tracked target not assigned with detection. Suppose $i$-th target starts to be occluded in frame $t'$ and finishes occlusion in frame $t$, where $t - t' > 1$, $\mathbf{b_1} = (\xi_1, \zeta_1, \omega_1, \eta_1)$ is the bounding box associated with the first location specified by its $x$-coordinate, $y$-coordinate, width and height respectively, and $\mathbf{b}_2$ is for the second location.  We can calculate the following feature for estimation,
$$\Big[t-t', \frac{\xi_2 - \xi_1}{\bar{\eta}}, \frac{\zeta_2 - \zeta_1}{\bar{\eta}}, \frac{\eta_2 - \eta_1}{\bar{\eta}}, \mathrm{IoU}(\mathbf{b}_2, \mathbf{b}_1), \phi_{hist} \Big],$$
where $\bar{\eta}  = \frac{\eta_ 1 + \eta_ 2}{2}$ and $\phi_{hist}$ is histogram intersection of the two image patches bounded by $\mathbf{b}_1$ and $\mathbf{b}_2$. In the tracking phase, for those $^D\!x^{t}_{j}$ not assigned to any  $\hat{x}^{t - 1}_{i}$ and those $\hat{x}^{t'}_{i}$ not being assigned with any  $^D\!x^{t}_{j}$, the SVM classifier is used to estimate the matching possibility of each pair. Hungarian algorithm is employed to find the final matching pair.

\noindent\textbf{Target Enter} As mentioned above, if $^D\!x^{t}_{j}$ hasn't been assigned in any of the previous stages, $^D\!x^{t}_{j}$ is added to $\hat{\bm{X}}_{t}$ as a new target.

\noindent\textbf{Target Exit} We adopt two criteria for target exit checking: i) Bounding box of $\hat{x}^{t}_{i}$ is out of view. ii) Target hasn't been assigned a detection for continuous $T_V$ frames.

\section{Experiments}
\label{exp}
We conduct three experiments on the popular MOT15 \cite{leal2015motchallenge} and MOT16 \cite{milan2016mot16} benchmarks to analyze our proposed approach and compare to prior works. The test set of MOT15 contains 11 sequences and MOT16 contains 7 sequences, where camera motion, camera angle, and imaging condition vary greatly. For each test sequence, a training sequence is provided which is captured in the similar settings. For both training and test set, detections from a real detector are provided.

\begin{table*}[!t]
	\small
	\begin{center}
		\caption{Tracking Performance on the MOT15 benchmark test set. Best in bold.}
		\label{table:res15}
		\begin{tabular}{c|ccccccccc}
			\hline\hline
			Mode & Method & MOTA$\uparrow$ & MOTP$\uparrow$ & MT$\uparrow$ & ML$\downarrow$ & FP$\downarrow$ & FN$\downarrow$ & IDS$\downarrow$ & Frag$\downarrow$ \\
			\hline

			\multirow{6}{*}{\rotatebox{90}{\textbf{Offline}}}
			& TBD~\cite{geiger20143d} & 15.9 &	70.9&6.4\% &	47.9\% &14943&	34777&1939&	1963 \\

			&CEM \cite{milan2014continuous}& 19.3& 70.7& 8.5\%& 46.5\%& 14180 &34591 &813 &1023 \\

			&JPDA\_m \cite{rezatofighi2015joint}& 23.8 & 68.2& 5.0\%& 58.1\%& \textbf{4533}& 41873 &\textbf{404}& \textbf{792} \\

			& SiameseCNN \cite{leal2016learning}& 29.0& 71.2& 8.5\%& 48.4\%& 5160 &37798& 639& 1316 \\

			& MHT\_DAM \cite{kim2015multiple}& 32.4&71.8&16.0\% &43.8\% &	9064 &	32060&	435&826       \\

			& JMC \cite{keuper2016multi}&\textbf{35.6}&\textbf{71.9}&\textbf{23.2\%} &\textbf{39.3\%} &10580 &\textbf{28508} &457	&969	 \\
			\cline{1-10}

			\multirow{6}{*}{\rotatebox{90}{\textbf{Online}}}
			&RNN \cite{milan2017online}& 19.0	&71.0&	5.5\%&	45.6\% &11578&36706&	1490	&2081 \\

			&oICF \cite{kieritz2016online}& 27.1&70.0	&6.4\% &48.7\% &7594&36757&	\textbf{454}	&1660 \\

			& SCEA \cite{hong2016online}& 29.1	&71.1	&	8.9\% &	47.3\% &6060&	36912	&604&	\textbf{1182} \\

			& MDP \cite{xiang2015learning}& 30.3& 71.3& 13.0\%& 38.4\%& 9717 &32422 &680 &1500       \\

			& AP \cite{long2017online}&38.5& \textbf{72.6}& 8.7 \%& 37.4\%& \textbf{4005} &33203 &586 &1263 \\

			& proposed & \textbf{38.9}  & 70.6 & \textbf{16.6\%} & \textbf{31.5\%} & 7321	& \textbf{29501}	& 720 & 1440  \\

			\hline\hline
		\end{tabular}

	\end{center}

\end{table*}

\begin{table*}[!t]
	\small
	\begin{center}
		\caption{Tracking Performance on the MOT16 benchmark test set. Best in bold.}
		\label{table:res16}
		\begin{tabular}{c|ccccccccc}
			\hline\hline
			Mode & Method & MOTA$\uparrow$ & MOTP$\uparrow$ & MT$\uparrow$ & ML$\downarrow$ & FP$\downarrow$ & FN$\downarrow$ & IDS$\downarrow$ & Frag$\downarrow$ \\

			\hline
			\multirow{6}{*}{\rotatebox{90}{\textbf{Offline}}}
			& SMOT \cite{dicle2013way}& 29.7 &	75.2&	5.3\% &	47.7\% &	17426	&107552&	3108&	4483	 \\

			&CEM \cite{milan2014continuous}& 33.2&75.8&	7.8\% &	54.4\% &	6837&114322&	642	&731 \\

			&GMMCP \cite{dehghan2015gmmcp}& 38.1 &	75.8&	8.6\% &	50.9\% &	6607&	105315	&937&	1669 \\

			& MHT\_DAM \cite{kim2015multiple}& 45.8 &	76.3&	16.2\% &	43.2\% &	\textbf{6412}&	91758&	590&	781       \\

			& NOMT \cite{choi2015near}& 46.4	&76.6	&\textbf{18.3\%} &41.4\% &	9753&87565	&\textbf{359}	&\textbf{504}       \\

			& LMP \cite{tang2017multiple}&\textbf{48.8} &	\textbf{79.0} & 	18.2\% &	\textbf{40.1\%} &	6654&	\textbf{86245} &	481&595	 \\
			\cline{1-10}

			\multirow{5}{*}{\rotatebox{90}{\textbf{Online}}}
			&OVBT \cite{ban2016tracking}& 38.4	&75.4&	7.5\% &	47.3\% &	11517 &	99463 &	1321 &	2140	 \\

			& EAMTT	\cite{sanchez2016multi}& 38.8 &	75.1	&	7.9\% &	49.1\% &	8114&102452&965&	1657	 \\

			& oICF \cite{kieritz2016online}& 43.2 &	74.3&11.3\% &	48.5\% &	6651&	96515&	\textbf{381}&	1404       \\

			& AMIR \cite{sadeghian2017tracking}&47.2&	\textbf{75.8}&14.0\% &	41.6\% &	\textbf{2681}&92856&	774&1675 \\

			& proposed & \textbf{48.8} & 75.7   & \textbf{15.8\%} &	\textbf{38.1\%}&	5875&	\textbf{86567}&	906&	\textbf{1116}  \\
			\hline\hline
		\end{tabular}

	\end{center}

\end{table*}

\subsection{Experiment Setting}

The proposed approach is implemented in MATLAB with Caffe and running on a desktop with 4 cores@3.60GHz CPU and a GTX1080 GPU. We use PAFNet proposed in \cite{cao2017realtime} for $\bm{T}_{\mathrm{det}}(.)$. PAFNet generates two feature maps at the end, where different human body parts and corresponding affinity field are highly responded. Two feature maps are concatenated along channel to form the output of $\bm{T}_{\mathrm{det}}(.)$. We use $\bm{T}_{\mathrm{det}}(.)$ to distinguish pedestrian from their background. PartNet proposed in \cite{zhao2017deeply} is adopt for $\bm{T}_{\mathrm{id}}(.)$. PartNet generate $L2$ normalized feature for person Re-Identification task, which is suitable for $\bm{T}_{\mathrm{id}}(.)$ to distinguish different pedestrians. Original PartNet outputs a feature vector for each input image. We remove its last global pooling layer and convert the last fully connected (FC) layer to convolutional layer to output feature map in reasonable dimensions.

For each test sequence in MOT15 and MOT16 dataset, one or more similar sequences in training set are used to train a CNN classifier mentioned in Sec.~\ref{model_refresh} and a SVM classifier in Sec.~\ref{targ_m}. We adopt the partition method mentioned in \cite{xiang2015learning}. CNN classifier is consisted of one convolutional layer and one FC layer. When training the CNN classifier, $B_N = 32$ and 5 iterations with constant learning rate of 0.001 are used when CNN classifier makes mistake.

By implementing IA tracker and model refreshment with shared feature extraction as shown in Fig.~\ref{fig:tracking}, the average speed of proposed approach on MOT15 dataset is about 0.3 fps and 0.1 fps on MOT16 dataset. The average target densities on each frame of those two datasets are 10.6 and 30.8 for the test set. Proposed method achieves acceptable speed performance compared with other methods such as LMP (offline)\cite{tang2017multiple} at 0.6 fps and AMIR (online)\cite{sadeghian2017tracking} at 1.0 fps.

\noindent \textbf{Evaluation Metric} To evaluate the performance of proposed method, we employ the widely accepted CLEAR MOT metrics \cite{bernardin2008evaluating}, including multiple object tracking precision (MOTP) and multiple object tracking accuracy (MOTA) which is a cumulative measure that combines false positives (FP), false negatives (FN) and the identity switches (IDS). Additionally, we also report the percentage of mostly tracked targets (MT), the percentage of mostly lost targets (ML), and the number of times a trajectory is fragmented (Frag).

\subsection{Determine $T_V$}
\label{sec_tv}
Hyper-parameter $T_V$ in proposed approach is used to determine the maximum continuous frames that a target can be tracked without the verification from external detection. Setting of $T_V$ controls the strength of awareness between target models: As $T_V$ increasing, verification becomes less frequent, each target model tracks its target more independently, which is more equivalent with directly applying multiple SOT tracker for MOT; When decreasing $T_V$, proposed approach depends more on external detection and behaviors more like traditional tracking-by-detection approaches. As reflected in evaluation metrics, choice of $T_V$ controls the trade off between FP and FN. Higher $T_V$ allows tracker to continue more frames without the confirmation from detection, thus may introduce more FP. Lower $T_V$ requires frequent verification between tracker and detection, where tracking performance will heavily depend on detection quality, thus tracker may generate more FN when detection quality gets worse.

We test various of $T_V$ on the training dataset of MOT benchmark. The results of MOTA, FP and FN for Venice-2 from MOT15 and MOT16-05 from MOT16 are reported in Tab.~\ref{tab_tv}. In both sequences, starting at $T_V = 0$ where verification for every frame is required and increasing $T_V$, MOTA first increases then decreases due to the increasing FP in results. FP and FN gain their balance at $T_V = 4$ for Venice-2 and $T_V = 5$ for MOT16-05 where MOTA achieves best. We choose $T_V = 4$ for the rest of our experiments.

\begin{figure*}[!h]
	\small

	\centering

	\begin{tabular}
		{c@{\hspace{0.3mm}}c@{\hspace{.4mm}}c@{\hspace{.4mm}}c@{\hspace{.4mm}}}%

		\includegraphics[width=0.195\linewidth]{fig/fig4/pets.jpg}    & \includegraphics[width=0.26\linewidth]{fig/fig4/ad1.jpg}    & \includegraphics[width=0.26\linewidth]{fig/fig4/ad3.jpg}    &
		\includegraphics[width=0.26\linewidth]{fig/fig4/town.jpg}
		\\
		PETS09-S2L2& ADL-Rundle-1 & ADL-Rundle-3 & AVG-TownCentre
		\\
		\includegraphics[width=0.195\linewidth]{fig/fig4/06.jpg}   & \includegraphics[width=0.26\linewidth]{fig/fig4/03.jpg}   & \includegraphics[width=0.26\linewidth]{fig/fig4/12.jpg}   &
		\includegraphics[width=0.26\linewidth]{fig/fig4/14.jpg}\\
		MOT16-06 & MOT16-03 & MOT16-12 & MOT16-14\\

	\end{tabular}

	\caption{ Visualization of selected sequences. The first row is from MOT15 test set, the second row is from MOT16 test set. Trajectories are fitted for better view.}
	\label{fig_results_vis}
\end{figure*}
\subsection{Ablation Study}

We justify the effectiveness of each building block in proposed method through ablation study as shown in Tab.~\ref{tab:ab}. IA stands for the proposed instance-aware tracker. MR is the dynamic model refreshing. IA$-$DV disables detection verification in IA tracker by setting $T_V \to \infty$, which removes the awareness between target models thus is equivalent with applying multiple independent SOT trackers for MOT. IA$-$TA disables target level awareness by replacing the fusion features with general deep features extracted from VGG-16 trained on ImageNet. Full method also includes the re-tracking and occlusion handle part.

Analysis is performed on Venice-2 sequence from training set of MOT15. Numerical results of all CLEAR MOT metrics are listed in Tab.~\ref{tab:ab}. Having demonstrated the importance of awareness between target models in Sec.~\ref{sec_tv}, totally disabling detection verification results in the greatest performance degradation. Model refreshment is also essential for improving performance and robust tracking. As shown by MOTA and MOTP, with model refreshment, not only tracking accuracy but also the bounding box precision improves a lot. In Full method, re-tracking and occlusion handle mechanism use simple linear interpolation to estimate the missing locations between the previous tracked target and current detection, which may introduce FP, but reduces more FN as shown in Tab.~\ref{tab:ab} thus still improves the overall performance.

\subsection{Results on Test Sequences}

We test our proposed approach on both MOT15 and MOT16 test sequences. In order to boost performance, we adopt several pre- and post- processing techniques, including excluding detections with extreme size according to scene prior and applying fitting to result trajectories in sequences where no rapid pedestrian scale changes. The performance is shown in Tab.~\ref{table:res15} and Tab.~\ref{table:res16}. We compared our method with the best peer-reviewed and published results on the benchmark, including JMC~\cite{keuper2016multi}, AP~\cite{long2017online}, LMP~\cite{tang2017multiple} and AMIR~\cite{sadeghian2017tracking}.

The biggest challenge in MOT15 and MOT16 datasets is the enormous FN over FP (more than 10 times in MOT16) as shown in  Tab.~\ref{table:res15} and Tab.~\ref{table:res16}, which is partially introduced by FN in public detection. Benefited from the built-in SOT techniques, proposed method results in the least number of FN and the best MT/ML performance compared with all other online methods. As for overall performance, we established a new state-of-the-art among all online and offline methods in both MOT15 and MOT16 benchmark in terms of MOTA which is the most important metric for MOT. Visualization of selected sequences is shown in Fig.~\ref{fig_results_vis}. The complete metrics and visualization can be found on the benchmark website.\footnote{\url{https://motchallenge.net/results/2D_MOT_2015/} and \url{https://motchallenge.net/results/MOT16/} referred as `KCF'.}

\section{Conclusion}
\label{conclude}
In this paper we proposed using instance-aware with SOT technique to improve multiple object tracking (MOT). By built-in instance-awareness both in each target model and between all target models, our proposed approach can better predict the location of each target online, and meanwhile conserves the uniqueness of each tracking model to prevent the generation of duplicated and false positive trajectory. Tracking models in our approach are refreshed dynamically with a learned convolutional neural network to inhibit the noise of using inaccurate detections and to adapt appearance and scale variation of targets over time. Experiments on the MOT15 and MOT16 challenge datasets show the effectiveness of proposed approach in comparison with state-of-the-art.

{\small
\bibliographystyle{ieee}

redpajama_set_name: RedPajamaArXiv


text:
Magnus Nilsson Uses Traditional Methods to Update Nordic Cuisine
Mina Kim
(Erik Olsson)
To get to chef Magnus Nilsson's remote 16-seat restaurant Faviken, diners have to travel 200 miles south of the Arctic Circle in Sweden. The 18th century barn housing Faviken lies in foraging country, where Nilsson uses traditional methods for preserving foods and serves up dishes like reindeer lichen and scallops cooked over burning juniper branches. We'll talk to Nilsson about what it's like to run a restaurant considered one of the best in the world, discuss his new cookbook on Nordic cuisine and find out what it was like being featured in PBS' "The Mind of a Chef."
Magnus Nilsson, chef at Faviken in Sweden; author of "The Nordic Cookbook"; featured in the PBS series "The Mind of a Chef" and the Netflix documentary series "Chef's Table"


As an online retailer, we are responsible for detecting and preventing credit card fraud. If we did not do this, we would not be permitted to continue offering Paypal or credit cards as payment options.
Purchases and accounts in our system are checked daily for potentially fraudulent activity. Accounts that are deemed potentially compromised are flagged for Kongregate staff review. If the staff person is unable to determine the original owner of an account based on account information and recent payment details, we send a notice to the email address listed on the account. The account owner must contact us to verify the recent purchases made on the account.
If we do not receive verification within 5-7 days of the email, we may temporarily ban your account in order to force contact.
If we still do not receive verification that clears the account within 5-7 days after that, the account may be permanently banned and the recent purchases under review may be refunded.
How do I verify the purchases on the account?
A comment that states the purchases on the account were authorized by them.
PLEASE NOTE: If you used a gift card to make a purchase we are asking you to verify, please have the person listed on the gift card contact us to verify the purchase.
Can an account that has been permanently banned for "purchasing issues" due to failure to verify potentially compromised payments be recovered?
No - accounts banned for this reason cannot be recovered.


Today - I was seeing the end of sanding-filling-sanding-filling sanding etc etc the hull of my power skiff in order to finally paint it.
As the last action, I glued the finished floor cleats to the finished floor, temporarily fixing them with a nail gun. Despite beforehand trials as to the correct length of the nails I noticed afterwards that some of the nails must have gone through to the fibreglass, which created quite a few areas where the fibreglass was lifted off the the hull, but not actually perforating the fibreglass. The diameter of these areas is roughly 1 cm.
What should I do? Sand over and paint as if nothing had happened or take off the fibreglass from the affected areas and start filling them?
Needless to say: this is very annoying, but that's how it is!
I think that I would cut out the delaminated area. Sand the edges. Then make at patch that overlaps the hole. Sand its edges then fill coat it and sand some more.
4). PITA now, but you'll kick yourself later if you don't fix it properly now.
5). We have all been there and done that in some way or another.
...thanks everbody. As soon as I have stopped kicking myself for damaging the result of several weeks' labor in a couple of minutes, (...should be done by about noon ...) I shall proceed as suggested.
To quote Bill There can be no miracle recoveries without first screwing up.


text:
Marlon Ventura (NJ, USA): Marlon is a seasoned angler chasing multiple species in the Northeast. He is passionate about light tackle fishing and taking light gear to the upper limit. Marlon enjoys the pursuit of trophy striped bass, fluke, blackfish, and a variety of other bottom fish. If he isn't striper fishing, you'll often find Marlon on a jetty or boulder field with a couple dozen crabs ready to feed the tautog.
Team Captain
Scott Davis (NJ, USA): Scott Davis is an avid surfcaster whose excitement for the sport is contagious. He has chased striped bass year-round from the back-bays of New Jersey, where he calls home, to the northern waters of Cape Cod. Aside from striped bass, Scott enjoys targeting early spring bluefish on the flats and can often be found teasing these toothy torpedoes with a variety of top water poppers. Scott takes great pleasure sharing his knowledge and experience on tackle and gear.
Team Captain/Public Relation
John Johnson (NJ, USA): John has a enjoyed a lifelong love for surfcasting and all types of fishing, growing up in New Jersey chasing Bass, blues, fluke, and all freshwater species from a very young age. When hes not behind a stove, he most enjoys plying the night tides for trophy striped bass with plugs and eels up and down the Striper Coast. His passion for fishing has taken him from Texas to New England to the offshore canyons, always in pursuit of a bent rod.
Team Event Coordinator
Khanh Nguyen (NJ, USA): Khanh is a passionate all around angler from boat and surf. He's most at home on a rock in the middle of the night on Block Island catching bass without another soul around for miles, or walking the sandy beaches at night pitching lures into the whitewater. When he's not chasing stripers on the surf around the Northeast, Khanh can be found on his boat pursuing trophy fluke, seabass and blackfish.
Team Field Tester/Promoter (MA, USA)
Colby Brouillette (MA, USA): Colby is an experienced angler who loves all aspects of trophy striper fishing from shore. He is a mostly catch and release fisherman. He has spent the last 30+ years successfully targeting big stripers from the Cape Cod Canal and Cape Cod beaches. Colby is a versatile angler who loves tactics such as eeling from the beach to throwing topwater lures for explosive hits. Above all, his favorite way to target big bass is drifting jigs in the deep, fast moving.
Team Promoter/Educationer
Bernie Hoyt (Long Island, NY, USA) Bernie Hoyt has had a passion for surfcasting his entire life, beginning with his father introducing him to the beaches of Fire Island, Long Island's South Shore, and Montauk. He is an New York State Certified Fishing Guide with over 30 years experience in the surf as a fisherman and as an educator. Bernie has guided anglers to various Long Island beaches and inlets, as well as to Cape Cod, Cuttyhunk Island, and other Striper Coast locations.
Team Field Tester/Promoter
Daniel Rodriguez (Florida, USA): Daniel Rodriguez hails from Melbourne, Florida and pursues trophy Redfish, Snook, and Tarpon from the surf, waterways and lagoons of Florida. After landing his first Redfish, he was hooked for life. Daniel enjoys sharing what he's learned with his friends and family, watching their excitement when they land trophy fish. In the dead of the night, you can find Daniel out on the surf, listening to waves crash while Snook and Tarpon are busting baitout of the water
Christopher Pepice (CT, USA): Chris is an experienced angler who loves to test out new products. His knowledge in fishing tackle from freshwater to saltwater is impecable. Chris true passion is catching stripers all year round in the New England area. He is most at home walking the rivers and beaches in Connecticut casting light jigs to lures. You can often find Chris targeting trophy stripers at the cape cod canal.
Tony Skojec (CT, USA): Tony is a veteran all around fisherman. His passion began as a young boy. Starting with chasing stripers, bass, and fluke, and has taken him to the offshore canyons chasing Giant Bluefin tuna, and plying the frigid northern waters for elusive and challenging steelhead. Tony has a passion for chasing Trophy Striped bass all over the Striper coast, particularly in the cape cod canal, and by boat in the Northeast's finest striper havens. He brings a wealth of knowledge.


Our skilled Amazon Consultants will help you launch and strategize your brand or business to gain more branding power and sales through Amazon.
Amazon's burgeoning marketplace dominates the online consumer market and it comes as no surprise that it has recently become a new channel of distribution for fashion wholesalers and distributors. However, selling on Amazon has its own unique challenges and special marketing tactics are often needed to succeed. In order to establish a good foundation for your company to build upon in later years, we have created an exclusive individualized program that moves you through each step at a pace you can follow. At your initial consultation you will have the opportunity to convey your goals and current business model to one of our consultants who will in turn discuss your options with you. When you are ready, we can help you setup your Amazon storefront according to your specifications and assist you with photography, content, and other marketing services you may require.


text:
Palm Reader
Palmistry has been present since caveman era. Archaeologist have discovered many hand print made out of stone, wood and ivory. The discovery revealed the fascination ancient civilization had on the details of the palm, it was believed that palm was the path of connection with god and also a healing tool. Palmistry was first used by Egyptians, Chaldeans and India, later it had spread to China, Tibet, Persia and other places in Asia and Europe. Palm reading was conducted by gypsies since 3000 BC. Alexander the great, had made decisions based on the reading of his sword, his sword makers were gypsies who were also fortune tellers. Palm reading was always praised until organized religion had bad mouthed it. However, palm reading is still popular amongst people. Psychic shops can be found everywhere, for example, in Atlantic City boardwalk, there are about one to two psychic shops in every block. People turn to palm readers to uncover their future, many find it comforting to know what will happen in the future. People are always seeking answers to question like what they are meant to do in their life? Who will be their significant other and when? This curiosity led them to believe palm readers.
One day at work I was helping out a client, who was a palm reader. When she stepped to the register, she started making statements about my manager who was scanning her clothes she was purchasing. My manager stopped and all of his attention drifted towards her as soon as she had mentioned about a relationship in Florida. She had said that he had a relationship in Florida, but he had told her that he had never been to Florida. After that statement, she immediately changed it and mentioned he will get a better job in February. When he heard that he started believing everything that she had said about him through palm reading. He was in love with the idea of getting a better job, so he wanted to believe her. He had given her that money, so she would be more detailed about the reading. In the middle of the reading she had held his hand and passed him a rock, which would give him positive energy and wanted to charge him $50 for the rock. Of course he denied, since he will not give her money for the rock, she wanted him to help them steal from the store and pay for the rock, but he refused and asked them to leave the store. When this was all happening, my main focus was strictly on the behavior of the psychic, who seemed very aggressive. She had a very dominant attitude, which affected the confidence of my manager. This dominant trait is what allows them to convince people that palm readers are special. They specialize in scamming people by attacking their emotion.
Posted by Shahana Salam at 4:27 PM
Jeanine (Nhi) Ho November 9, 2014 at 8:17 PM
I love how Palm Readers would advertise that a palm reading would only be $5, ONLY $5. The trick is between the fine lines. It starts off at $5 then while they've caught your emotions, there are add-on services. This process all results in $50+. It really is a scam just to hear negativity or bluffs.
The lie detector determined that was a LIE!
Madden Curse
Long fingered Alien Friends?
The Full Moon
James VanPraagh: Medium of the Century
Music... Help or no Help?
In Major League Baseball, there are many different...
Why Do Little Girls Love Fairies?


NEBHE offers cost containment strategies in insurance and technology. All education institutions or agencies in New England can participate.
NEBHE's Policy & Research team seeks to support innovation, engage conversation and drive change by providing timely information, research and analysis on issues related to higher education and workforce development to decision-makers and the public throughout New England.


text:
Q: Advanced Python string formatting with custom placeholders? I have the following HTML template in a Python variable:
template = """
    <script>
        function work()
        {
            alert('bla');
        }
    </script>

    Success rate is {value:.2%} percent.
"""

I want to substitute {value:.2%} with some decimal number with the appropriate formatting. Since my template may contain a lot of JavaScript code, I want to avoid escaping the curly braces with {{ and }}, so using template.format(...) directly is not an option.
Using Template(template).substitute(...) also seems impossible because I want advanced formatting for value.
I could probably replace {value:.2%} with a corresponding %(value)... syntax and then use template % .... But I'm not a fan of this syntax because most of the variables in a real-world template won't need advanced formatting, so I want to keep the placeholder syntax simple.
So my question is, is it possible to use custom placeholders in the template that would allow for advanced formatting when necessary, i.e. to have simply {{value}} or [[value]] but also {{value:.2%}} or [[value:.2%]] ?
Edit: Finally, I want to avoid errors that .format(...) would produce when the template contains placeholders, such as {{dont_want_this_substituted}}, for which the passed dictionary doesn't contain a value. That is, I want to only substitute only certain placeholders, not all that appear in the template.
Edit 2: To achieve what I want, I can grab all placeholders with a regular expression first, then format their contents and finally make the replacement in the template. But I wonder if an easier solution exists.
Edit 3: It was suggested that I split the template to avoid issues with format(). I would like to avoid this, however, because the template actually comes from a file.

A: Simply preprocess your template.  For example, if you want [[...]] to be your template markers and leave single { and } characters alone:
template = """
    <script>
        function work()
        {
            alert('bla');
        }
    </script>

    Success rate is [[value:.2%]] percent.
"""

result = template.replace("{", "{{").replace("}", "}}").replace("[[", "{").replace("]]", "}").format(value=0.8675309)

Trying to do it all with varying numbers of curly brackets is tricksy, so I would definitely use some other characters. Careful, though, things like [[ and ]] could reasonably occur in legitimate JavaScript code. Might be better to use something that never could.

A: Forget regex and preprocessing. You should break up the template so that the variable parts aren't in the same string as the <script> parts.
head = """
    <script>
        function work()
        {
            alert('bla');
        }
    </script>
"""

template = """
    {head}

    Success rate is {value:.2%} percent.
"""

Finally, I want to avoid errors that .format(...) would produce when the template contains placeholders, such as {{dont_want_this_substituted}}, for which the passed dictionary doesn't contain a value. That is, I want to only substitute only certain placeholders, not all that appear in the template.

It might be hacky, but you can use collections.defaultdict, as shown in this answer. Code sample from that answer (modified).
from collections import defaultdict

my_csv = '{optional[first]},{optional[middle]},{optional[last]}'
print( my_csv.format( optional=defaultdict(str, first='John', last='Doe') ) )

redpajama_set_name: RedPajamaStackExchange


Stream fullscreen video directly to any browser in your WiFi network.
This giveaway offer has expired. Pixatar is now available on the regular basis.
Instant Webcam can stream fullscreen video to multiple devices in the same Wifi Network.
Works with all modern browsers, including Firefox, Safari, Chrome, Opera, Internet Explorer, Mobile Safari and Chrome for Android.


CompuScapes provides high quality, innovative automation solutions for the Green Industry.
We want to give our customers our best possible service. We strive to treat each one with fairness, respect and honesty. We endeavor to be helpful, go the extra mile, and listen to them. Because by knowing our customers, we can better serve them. Our customers' success depends on our products, so we do our utmost to make our software the best it can be.
CompuScapes was founded in 1989 by Tim Shields. Tim recognized a need in the landscape industry for a quality, cost-effective business management software program. Working with experienced landscape contractors, Tim developed CompuScapes software.
From the original concept that most landscape contractors needed more than a general accounting package, an estimating, work order, invoicing, accounts receivable and job-costing system was born. Additional enhancements included routing and scheduling; employee time accounting; accounts payable; general ledger and financial statements; inventory control and purchase orders; and an interior plant care module.
Tim has over 30 years of experience in accounting software development. His skills include analysis, design, programming and system implementation. He holds a degree in Computer Science and Business from Southern Adventist University. Tim has provided technical consulting services for small and large companies. His communication and interpersonal skills provide a bridge between technical and non-technical personnel.


Further Options. During the purchase of the cabinet doors you can also buy the necessary veneer to apply to your cabinet face frames and exposed ends. This veneer material is available with an adhesive back, a remove and stick affair. You can buy it in raw hardwood and apply a get in touch with cement to both the kitchen cabinet and the veneer. I do recommend that approach for most DIYers its messy and there are not much savings over the peel and stick veneers. Along with your drawer door purchase you may also prefer to replace the cabinet bathroom drawer boxes, other options include get or roll out drawers, racks, etc . These are great storage space and back saver alternatives. One thing the company I use has that can be hard to find is custom made bread boards. This is best for replacing the old nasty broken plywood breadboards that come with several homes. Although it seems to be a fading trend to have constructed in bread boards there are some people who really like them and nothing tones a solid hardwood bread mother board, if built from quality wood they will last a lifetime. There a so many other options such as organizer trays for silverware, junk bins, that I simply is not able to list them all here, yet I would like to make you aware of these people prior to tackling a refacing project so that you can perhaps further research them and see this they may fit your needs.
Veterinariancolleges - Naturino boys 4680 casual chukka boots. Naturino boys 4680 casual chukka bootsmanmade solemade from quality materialsimportednaturino european brand known for style, comfort, and great. Naturino kids 2931 fashion chukka boots. Buy naturino kids 2931 fashion chukka boots at boys shoes all boys shoes naturino naturino kids 2931 fashion chukka boots average rating: 0 out of 5 stars, based on 0 reviews write a review naturino this button opens a dialog that displays additional images for this product with the option to zoom in or out. Naturino girls 4528 fashion lace up chukka boots. Buy naturino girls 4528 fashion lace up chukka boots and other boots at our wide selection is eligible for free shipping and free returns. Naturino boys 4680 casual chukka boots. Naturino boys 4680 casual chukka boots home; boys; naturino boys 4680 casual chukka boots. Naturino naturino boys 4680 casual chukka boots. Naturino boys 4680 casual chukka boots

manmade sole
made from quality materials
imported
naturino european brand known for style, comfort, and great fit
comfortable great for everyday wear about this item. Naturino naturino girls 4528 fashion lace up chukka boots. Save money on naturino girls 4528 fashion lace up chukka boots! we've found the best winter deals naturino kids boots & booties; naturino naturino girls 4528 fashion lace up chukka boots connexity more photos $ at walmart see it now naturino girls 4528 suede chukka boots all about. Naturino boys' shoes shopstyle. Find naturino boys' shoes at shopstyle shop the latest collection of naturino boys' shoes from the most popular stores all in one place naturino choco chukka boot $ get a sale alert free shipping & free returns at zappos naturino hasselt vl ss19 toddler little kid $. Naturino suede shoes for boys ebay. Naturino tan beige suede leather upper chukka style ankle boot with velcro fasteners these are a quality lair of shoes made in italy the soles and velcro are in very good condition there are two darker areas of suede on one shoe that are barely visible please review photos carefully these shoes are easy for young kids to put on independently. Boys' shoes: boots sears. Freeman boys' sawyer chukka boot sold by sears $ $ joseph allen boys' lace up boot black naturino boys 2931 dessert casual bootie sold by shoe pulse $ $ joseph allen boys' lace up boot tan sears has a stylish collection of boys' shoes for your little man get him ready for any occasion with new casual. Hot sale: naturino girls 4528 fashion lace up chukka boots. Naturino boys 4680 fashion chukka boots see at walmart connexity easy to put on and stylish to boot, this suede chukka is perfect for school, weekend outings and everything in between joseph allen boy's casual lace up chukka boots saks fifth avenue off 5th on sale for $ original price $ $ $.