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Justia Lawyer Directory Entertainment & Sports Law Tennessee Cookeville Attorneys
Cookeville, Tennessee Entertainment & Sports Lawyers
Crystal M. Etue
Franklin, TN Entertainment & Sports Law Lawyer with 2 years experience
(615) 721-7983	202 4th Ave. S., Suite 202
Free ConsultationEntertainment & Sports, Divorce, Estate Planning and Family
Southern University Law Center
Crystal Etue focuses her practice in matters related to family law, Probate and Entertainment. These areas allow her to incorporate two of her biggest passions; Arts & Entertainment and helping families in distress. Her services in the area of family law and probate include divorce, child custody, post-judgment modifications, wills and estate administration. With her experience as a veteran of the U.S. Air Force and TN Air National Guard as well as time spent working as a high school teacher, Crystal is uniquely prepared to handle family law cases with empathy, objectivity, common sense, discipline, patience, and a proclivity...
Todd G. Cole
(615) 490-6020	750 Old Hickory Blvd
Building Two #202
Brentwood, TN Entertainment & Sports Law Lawyer with 10 years experience
Entertainment & Sports, Business, Immigration and Personal Injury
Todd Cole, founder of Cole Law Group, has a diverse educational, business, and legal background that affords him a unique insight into the issues confronting our clients. He is recognized in the Nashville/Brentwood area for his outstanding academic background, keen mind, skillful representation, and dogged determination to serve his clients well. He is licensed to practice law in Tennessee, Florida, Minnesota, and the United States Middle District for the State of Tennessee. Todd received his Juris Doctor degree from Nova Southeastern University, where he was recipient of the Dean's Recognition Scholarship, granted the Book Award for Torts, acted as...
Marcus Shute Jr
Nashville, TN Entertainment & Sports Law Attorney with 4 years experience
(615) 953-4971	315 Deaderick Street
Entertainment & Sports, Business, Cannabis Law and Criminal
Nashville School of Law
Shute Law is a boutique law firm that utilizes a client-focused approach to create opportunities and procure sustainable contracts in the sports and entertainment industries. Our practice areas include contracts, litigation, consulting/business development, the cannabis & marijuana industry, as well as estate planning, criminal defense, and family law.
Chattanooga, TN Entertainment & Sports Law Lawyer with 8 years experience
Free ConsultationEntertainment & Sports, Business, IP and Trademarks
University of Tennessee - Knoxville
I am a Tennessee-licensed attorney and my practice focuses exclusively on assisting my clients with the acquisition, maintenance and enforcement of intellectual property, including patents, trademarks, and copyrights.
One of my primary roles is to identify potentially patentable inventions and the scope of protection available for those inventions. In this role, I regularly prepare, file and prosecute U.S. patent applications before the United States Patent and Trademark Office and also work with attorneys around the world in order to obtain foreign patent protection.
I also assist clients in identifying competing technologies that might limit the scope of their patent protection or...
G. Miller Hogan II
Nashville, TN Entertainment & Sports Law Lawyer with 25 years experience
(615) 726-0050	205 17th Avenue North
Entertainment & Sports, Business, Real Estate and Trademarks
I am a Commercial Real Estate & Business Attorney with extensive knowledge and experience in real estate, commercial and business transactions, non-profits, entertainment, sports and related litigation. I have broad experience with virtually all aspects of commercial real estate investment including tax deferred exchanges, leasing, commercial and residential development, real estate secured lending, workouts, foreclosures, special asset transactions, zoning and planning. I also work closely with many non-profit and tax-exempt organizations and churches in connection with planning and development challenges. I also have a well-established entertainment and sports law practice representing a number of high profile clients in...
Lawrence (Larry) Arnkoff
(615) 973-4570	5115 Maryland Way
Free ConsultationEntertainment & Sports, Criminal, Domestic Violence and White Collar Crime
There are several things I want potential criminal clients to know about me. I have more than 40 years of experience as a criminal defense lawyer in Tennessee and Florida. I represent clients who are being prosecuted or investigated for federal or state crimes. The majority of my practice is spent defending federal white-collar crimes, money laundering and drug trafficking. My considerable experience has allowed me to earn the respect of the Federal Judiciary, the U. S. Attorney's Office, the U.S. Marshal's Office, and all of the Federal law enforcement agencies (DEA, FBI, ATF, IRS, Homeland Security, etc.) in Middle...
Mr. Robin J. Gordon
(615) 933-2435	49 Music Square West
Entertainment & Sports, Business, Estate Planning and Family
University of Tennessee College of Law
Attorney Robin J. Gordon is the founder and managing partner at Gordon Law Group. Since 1990 Robin has called Music Row home for his firm. He was first introduced to private practice as an associate with a well-known litigation and entertainment firm in Nashville, TN. During his early years he represented artists such as George Jones, Ronnie Milsap, Tammy Wynette, and Garth Brooks. In 1996, Attorney Gordon created the Gordon Law Group with a focus on entertainment law, small business dealings, and litigation. With his new practice, Robin continued to represent record labels, publishing companies, and influential musicians, songwriters, and...
Cody Galaher
Nashville, TN Entertainment & Sports Law Attorney
(615) 651-7393	Fifth Third Center | Suite 2000
Free ConsultationEntertainment & Sports, Appeals, Business and Trademarks
Cody Galaher represents companies and individuals in litigation of state and federal matters primarily involving family, business, and appellate issues. Cody has wide-ranging and specialized litigation experience, both at the trial court and appellate levels, which he utilizes to obtain the very best possible outcome for his clients. Cody is experienced and has a reputation for obtaining great results for clients in divorce and custody matters.
Cody frequently helps clients form, govern, and operate their businesses and his distinct litigation expertise allows him to advise clients in avoiding and resolving potential disputes. In addition, Cody is also uniquely experienced in the...
Thomas David Ruth
(615) 244-7600	20 Music Square West, Suite 200
Entertainment & Sports and IP
Claimed Lawyer ProfileBlawgsearch
Christopher English Hugan
Hendersonville, TN Entertainment & Sports Law Lawyer with 16 years experience
(615) 669-7299	1191 W. Main Street
Serving Nashville's Entertainment and Business Communities. Nashville music and business lawyer. Professional musician and recording engineer for 15 years before attending law school. Office located in the beautiful Film House Building near downtown Nashville. Free consultations--call or email.
Bob Zeglarski
Nashville, TN Entertainment & Sports Law Attorney with 16 years experience
(615) 933-3545	3201 Dickerson Pike
Entertainment & Sports, Business and Securities
Seton Hall University School of Law and University of South Carolina School of Law
R. Mark Dougall
Franklin, TN Entertainment & Sports Law Lawyer with 26 years experience
(615) 369-8180	256 Seaboard Lane
Suite F103
Entertainment & Sports, Business, Estate Planning and Real Estate
Indiana University Maurer School of Law
Cynthia M Wood
(615) 321-0220	803 18th Avenue South
Entertainment & Sports, Business and IP
I'm an attorney at Gordon Law Group in Nashville, TN. My concentration areas are business, entertainment, and litigation. I enjoy working with people who earn a living in the entertainment industry.
Lawrence James Arnkoff
Free ConsultationEntertainment & Sports, Criminal, DUI and White Collar Crime
MJ Thomas
Hendersonville, TN Entertainment & Sports Law Attorney with 17 years experience
(615) 243-2118	Hendersonville, TN 37075
Entertainment & Sports, Consumer, Personal Injury and Probate
Noah C McPike Esq.
(615) 750-2207	1222 16th Ave. S
Nashville Entertainment Attorney
Denise Marie McIntosh
Nashville-Davidson (Balance), TN Entertainment & Sports Law Lawyer with 27 years experience
(615) 749-8306	1906 Acklen Ave
Nashville-Davidson (Balance), TN 37212
Peter L. Brewer
Knoxville, TN Entertainment & Sports Law Attorney with 32 years experience
(865) 224-8555	8903 Linksvue Dr
South Texas College of Law
Chattanooga, TN Entertainment & Sports Law Lawyer
(423) 757-5914	CBL Center, Suite 150
Entertainment & Sports, Antitrust, Business and IP
J. Scott Rudsenske
(615) 244-9501	3 McFerrin Ave
Entertainment & Sports, Administrative, Bankruptcy and IP
David Chase LanCarte
(214) 935-2430	2817 West End Ave
Entertainment & Sports, Arbitration & Mediation, Business and IP
Texas A&M University School of Law
Joseph Brazil
Entertainment & Sports, Communications and IP
Jack Rush Hicks
Nashville-Davidson (Balance), TN Entertainment & Sports Law Attorney
(615) 329-9455	49 Music Square W
James Randolph Smith
Berry Hill, TN Entertainment & Sports Law Attorney
(615) 386-7300	2735 Larmon Dr
Berry Hill, TN 37204
Andrea Patrice Perry
Nashville-Davidson (Balance), TN Entertainment & Sports Law Lawyer
(615) 238-6303	511 Union St
Entertainment & Sports, Business and Real Estate
David James Moser
(615) 498-3006	9 Music Square S
Denise McIntosh Stevens
(615) 749-8306	1906 Acklen Avenue
Joel Wesley Tisinger
Nashville-Davidson (Balance), TN Entertainment & Sports Law Attorney with 17 years experience
(615) 577-9603	1701 18th Ave S
Mercer Univ-W.George L.S
Robert Louis Crossley
Knoxville, TN Entertainment & Sports Law Lawyer
(865) 584-4040	1111 N Northshore Dr
Lawrence Anthony Sutter III
Franklin, TN Entertainment & Sports Law Lawyer
(615) 771-5008	341 Cool Springs Blvd
Entertainment & Sports, Business, Personal Injury and Products Liability
Tiffany Dunn
Tina Johns Benkiser
Signal Mountain, TN Entertainment & Sports Law Lawyer with 31 years experience
(512) 658-8378	PO Box 277
Signal Mountain, TN 37377
Entertainment & Sports, Bankruptcy, Business and IP
University of Alabama School of Law
Sidney Travis Bartee
3100 West End Ave
Entertainment & Sports, Estate Planning and Tax
Cumberland School of Law, Samford University
Paul Toby Housch
(615) 259-3313	222 2nd Ave N
Entertainment & Sports, Business, Criminal and DUI
Alfred Knight
Entertainment & Sports and Business
Alan Dale Johnson
Entertainment & Sports, Business and Personal Injury
Knoxville, TN Entertainment & Sports Law Lawyer with 23 years experience
(865) 560-4559	9721 Sherrill Blvd
Entertainment & Sports, Business, Communications and IP
Steve Byrd
Entertainment & Sports and Communications
Karl Braun
(615) 313-9913	611 Commerce St
Gregory Ramos
Entertainment & Sports, Business and Workers' Comp
Entertainment & Sports Lawyers in Nearby Cities
Entertainment & Sports Lawyers in Nearby Counties
Use Justia to research and compare Cookeville attorneys so that you can make an informed decision when you hire your counsel.

redpajama_set_name: RedPajamaCommonCrawl


Your mom was right to tell you to sit up straight though she may not have known the role it may play in increasing your confidence. In a new study out of Ohio State University researchers found that those with the best posture were more likely to believe thoughts about their qualifications for a job, than those who slumped.
The study included 71 students who were advised that they would be taking part in two separate studies at the same time. One was organized by the business school and the other one by the arts school. The participants in the art study were told that factors contributing to people's acting abilities would be measured. They were seated at a computer terminal and were told to either "sit up straight" and "push out [their] chest]" or "sit slouched forward" with their "face looking at [their] knees." For those in the business study while in these positions the factors that were examined were about job satisfaction and professional performance. At the completion, the participants took a survey in which they rated themselves on how well they would do as a future professional employee. The students graded themselves as future professionals based on which posture they held as they wrote the positive or negative traits. The results found that those with well-controlled posture were more willing to believe the information that they had written about themselves. Conversely, those who were sagging their chairs were less likely to believe their thoughts good or bad.
"Their confident, upright posture gave them more confidence in their own thoughts, whether they were positive or negative," Petty has said.
Here are a few exercises to keep your posture at it's best designed by Dr. Liz Welch a chiropractor and founder and CEO of PostureFit, a company that teaches people how to get strong and fit in their best posture.
Side Bending: Soften your knees and focus on your inner core. While keeping your back in a neutral position lower to one side then the other side. Continue this for ten reps per side.
OverHead Press: Place the posture bar behind the neck. Now press the bar straight up over the head with both hands then lower again to behind the neck and again, neck into bar into neck and keep soft knees.
Upright Tow: Start with the PostureFit bar across your hips with an open chest. Raise the bar with both hands up underneath your chin with slow intentional control and then lower again to your hips. Repeat ten times. Let's finish with a balance posture move with this same exercise. Narrow your base a little and put your left foot out to the side. Now using your balance, engage the core and do the same upright row five reps in that balanced position. Now switch to other side and lift right leg for five more reps.


text:
MAJORITY OF BOISEANS COMFORTABLE
RESUMING REGULAR ACTIVITIES
The following findings were produced as part of Embold Research's Omnibus—the only vehicle for hyper-affordable, bite-sized opinion research in Boise.
TO: Interested Parties
FROM: Julia Slisz, Embold Research
To inquire about purchasing the full results of this poll, including demographic breakdowns, contact nicole@changeresearch.com.
Residents of Boise are split in their opinions on the state of COVID-19, and have little trust in local government's ability to do what is right when it comes to managing the pandemic, according to a recent survey. The survey that fielded in mid-May reveals that over one-quarter of Boise adults report they are very unlikely to get a COVID-19 vaccine, despite Ada County outperforming the majority of the state in vaccination rates. And, while two-thirds feel at least somewhat safe travelling on a bus, train or plane, still 43% say they would feel unsafe attending a concert or sporting event.
Half (53%) of Boiseans express serious concerns about COVID-19, 30% expressing very serious concerns, with large gaps based on vaccination status. Of those who had already been vaccinated or say they are very likely to at the time of answering the survey, 71% express serious concerns, compared to just 26% of those who are unsure if they will get the vaccine, and 5% who say they almost certainly will not. Hispanic residents are slightly less likely to get a COVID-19 vaccine (30% unlikely, compared to 25% of white residents). This is despite Hispanic respondents being 10 points more seriously concerned about COVID-19 (62% to 52%), reflecting previously reported racial disparities in COVID-19 cases and vaccination rates among the Hispanic population in Idaho.
Of those who said they were very unlikely to get vaccinated, 205 survey respondents answered an open-ended question asking why. The most common reason is that the vaccine is "too new" or "not thoroughly tested." Many others express concerns about both short and long term side effects, and others that the COVID-19 vaccines that have been produced are not actually vaccines.
Although just 16% of these responses directly reference a lack of trust, distrust in the government, pharmaceutical companies, and the media is a common sentiment among many who say they won't get vaccinated. This compliments responses on trust in the local and national news media, as well as the federal government, which is significantly lower for those who are very unlikely to get vaccinated.
Majorities report feeling at least somewhat safe doing regular activities like taking public transit or attending a large concert or sporting event. Following the trend from a national survey conducted in March, those already vaccinated or very likely to be express the most concern about these activities. Women report 12 points more serious concern than men on COVID-19 in general (59% to 47%), and are more likely to report feeling unsafe partaking in these activities.
When asked about how funds from the American Rescue Plan's local funds should be used in Boise, the top priorities are providing aid directly to residents and to small businesses. These are the top two responses for every demographic, beating out providing aid to local nonprofit organizations, providing additional pay to essential workers, investing in water and sewer infrastructure, and investing in broadband infrastructure. When posed with a more general question about short-term versus long-term investments, responses are split with 48% preferring short-term aid, in order to reduce the negative impact of the pandemic now, and 52% opting for long-term investments, in order to make the eventual recovery stronger and faster. Proponents of long-term investments include men (56%), 18 to 34 year olds (56%), those with a college degree (60%), and people of color (63%).
This is Part 2 of a three-part series on public opinion and trust in Boise. The subsequent release will examine social and institutional trust.
Embold Research surveyed 924 adults online in Boise and Garden City between May 7–12, 2021. The modeled margin of error is 3.4%. Respondents were recruited to an online survey instrument via Dynamic Online Sampling, and post-stratification was done on age, gender, race/ethnicity, education, geography according to ACS 2015–19 five-year estimates of demographics of Boise and Garden City. Comparisons are to a national survey of 941 adults across the United States between March 18–30, 2021.
Join our email list to get notified when we release new polls in your area.
Embold Research is the nonpartisan, nonpolitical division of Change Research. Our methodology and polling have been featured in:


Dance me action game for Blackberry Touch.
Do the dance moves and get the trophies.
Do the combos and get trophies.
The game is very simple. Try clicking as fast as possible: Up, Down, Left or right keys at the bottom when matching icons appear near the triangle guy. Be careful: If you are slow or if you click the wrong key you will lose a life.
After you warm up the real dancing begins. There you can do special dance moves (trophies) if you know them. Each trophy will be shown if you reach the points needed. At the main menu, go to the trophies page to see how many points you need for each trophy. When the required points are gathered the trophy's icon first appears to alert you. After a while its four keys are shown to you. Hurry up and click the keys shown to activate it. If you are successful a trophy icon will appear, if not you will have to do this again when the trophy reappears.
If you have activated at least one trophy then the speed bar (next to the life dots) will be enabled. The bar will raise depending on the speed you click the correct keys. If you are fast, it will raise fast.
When the speed bar (next to the life dots) gets full it will enable the foot button (it will light up). You can click this button anytime you wish to do a dance move (trophy) you have already learned. Click it and then click the four arrow keys of your dance move (Go to the trophy page to remember them). If you click the foot button and successfully do a trophy, you can click the foot button repeatedly and get extra points until the trophy is over.
If you click the foot button and stop the dancing fellow with both his foot down on the ground then you will achieve a 'perfect sync' (see sync icon on the trophy icon). This way an extra arrow icon will appear at the end of the trophy (if successful) and by clicking it you will repeat the dance move. Repeating 4 times will give you a life.
A combo (that is to do another trophy right after one trophy ends) will be activated only after you do all the dance moves (trophies) you know. You must do them yourself (with the foot button). When you know many moves the combo will be repeated more than once. The trophies made while at combo count as moves for the future combos.
► Amazing frenetic fast gameplay!
► Designed for short gaming (breaks,metro).


text:
Metros with the most energy-efficient buildings | Entertainment News
The overwhelming majority of scientists agree that the world is facing a climate change crisis. Americans are deeply divided—largely along partisan political lines. They disagree about how impactful they believe climate change effects will be and what to do about it. But one area where there's more agreement is green construction, where tax breaks meet energy savings. In general terms, green construction, which includes the planning, designing, and constructing of an environmentally sustainable building.
One key measure of taking a green approach to building is being classified as Energy Star certified. Buildings in the United States may become Energy Star certified by exceeding a minimum score set out by the U.S. Environmental Protection Agency. This score is calculated based on energy usage and mapped against EPA tools, and must be renewed each year. There are unique and detailed criteria for single-family, multifamily, and manufactured homes.
Civil and landscape engineers also rely on Leadership in Energy and Environmental Design, or LEED, which encourages renewable materials, energy savings, and protection of biodiversity. Each phase of planning and construction has its own LEED rating system and scorecard, against which engineers can measure their efforts.
OhmConnect used the Environmental Protection's Agency's 2022 rankings to identify the metropolitan areas with the greatest number of Energy Star-certified buildings. The EPA identified the top 25 metros with the highest count of certified buildings as well as the top 10 in mid-size and top 10 in small metros. For comparison, the count of those metros with the most buildings are shown here based on the number of certified buildings per 1 million population. Because the EPA reports on just the top counts, some metros with fewer buildings but a higher rate per capita may not be listed here.


text:
Edition: IND
AUS edition
LAT edition
Leadership & Strategy
Industrial Data
TMMX Awards
Top 100 Awards
FASTForge to deliver cheaper aerospace titanium
Posted on 29 Nov 2016 by Jonny Williamson
A consortium comprising the world's leader in aircraft landing gear, a leading specialist metals producer and two of the UK's leading universities is working on FastForge, a project aimed at the production of aerospace-grade titanium at a third of the current price.
The partners working on the FASTForge project include Safran Landing Systems (formerly Messier-Bugatti-Dowty); Metalysis; the University of Strathclyde's Advanced Forming Research Centre (AFRC), and the University of Sheffield.
Through FASTForge, the consortium is aiming to produce novel titanium alloy aerospace components in three steps from rutile sand – a mineral composed primarily of titanium dioxide, found in plentiful quantities in Australia, South Africa and India.
The aim is to develop a novel low-cost titanium forging production process, unique to the UK, which could become a key enabler for the introduction of more titanium on aerospace components – leading to lighter aircraft and reduced emissions.
It will also enable the introduction or increased use of titanium, a light and non-corrosive material, in other industries such as rail, automotive, heavy duty construction and defence.
FASTForge will seek to develop the raw material process; establish how it can be embodied in a new UK supply chain; develop cost effective manufacturing techniques, and prove the capability in a landing gear application.
The FASTForge partners have tightly defined roles:
Safran Landing Systems will manage the project, provide the specifications for the component, test it and assess where else the process could be applied to their products.
Metalysis will create the powder titanium alloy from the rutile sand.
The AFRC, one of the seven elite centres which make up the High Value Manufacturing Catapult, and the University of Sheffield will model the manufacturing process steps and optimise the preform and forging die designs to minimise the material used in the end product.
The AFRC will also model and optimise the forging parameters and forge the final component shape. Together with Sheffield, the centre will also analyse the material properties of the intermediate and finished components to ensure they meet the stringent requirements of the landing gear application.
Michael Ward, CTO at the AFRC, explained: "The cost of titanium is an important issue in the aerospace industry.
"Cheaper titanium from the FASTForge process will protect the UK's position as the second-largest global aerospace manufacturer, with potential to grow our share of the market as the sector grows over the next 20 years. It will mean the supply chain staying and expanding in the UK with more high-value jobs as a result."
Sam Evans from Safran Landing Systems said: "The FASTForge process offers an exciting opportunity to reduce the costs and environmental impact of titanium production.
"This project has the potential to diversify the supply chain of titanium, allowing its use to continue in current products, as well as allowing its introduction into areas where it has not previously been feasible. This will provide a competitive advantage to the UK high value manufacturing and aerospace industry."
FASTForge is due to complete by mid-2018.
Lord Bilimoria says UK manufacturers are helping the country to rebound and rebuild our future post-Coronavirus
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Rare polish radio – produced only in 1939 with additional automatic motorised tunning to 12 programmed positions and with 4 step choice of selectivity granting extention of acoustic frequencies range depending on choosen selectivity. Serviced by author since 1965 today is in it's normal reception condition according to data. Tube EAB1 due to unproper operation replaced with EABC 80. EM 1 due to weak picture replaced with EM 4. Some faulty capacitors and resistors replaced with same but not original types.
Selctivity: 14 kHz, 11 kHz, 9 kHz, 7 kHz.
Outputs: Auxilirary speaker with transformer.
Actually due to lack of conditions for areal radio operates only with "grounding" antenna. With this conditins in the evening receives middle waves strong european stations like Praha, Budapest, Bucarest, Sweden. On long waves only Warsaw i Progrmm is heard. In short waves it is world range reception.
Presented below schematic diagramm is not a producer document but a result of record to "as seen" – not 100% may be according to factory diagram but author has no knowledge about this differences. His intention was to regain original circuitry and to present it.
Click drawing to see details and magnify.
INSIDE THE ELECTRIC AUTOMATIC – click photos and magnify.
Automatic device – panel of programmed push buttons. Visible electromagnet provides selfsupport to mechanical bar blocking the button in down position untill the desired position is met. With this moment motor stops, motor shaft moves axialy back to nonactive position by contact spring force, electromagnet coil voltage is off, bar is up and button is returned to up position.
Rear view of speaker. Most radios in this years had speakers with electromagnet. One of reasons was problem to obtain powerfull magnet field from solid magnets. Presented magnet was imported to Poland from England. Also the speaker diaphragm was imported from England.
Behind reconstructed by author steel plate in round cuts visible are 3 tunning air capacitors for two serial input filters and one for oscillator.
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The program is designed for actors of physical theatre, dancers, contemporary circus performers, choreographers and directors - performing arts practitioners with professional stage experience working in various genres, techniques and styles interested to find new international network opportunities and collaborators.
The programme includes intensive practical training and discussions guided by Sergei Ostrenko - Russian theatre director, choreographer and teacher, and Gennadiy Ostrenko - choreographer, movement director and theater artist.
The programme is focused on Ostrenko's method of actor's training, which is based on the Russian Theatre Tradition and newest experiments in physical theatre.
The practical training is focused on the psycho-physical approach to the art of acting relying on the teachings of Russian outstanding theatrical innovators - Vsevolod Meyerhold, Michael Chekhov and Konstantin Stanislavsky.
The Lab is a great opportunity to approach a unique methodological and practical material that will enrich your professional skills and will offer you the possibility to share an intense creative experience at a global level!
Sergei Ostrenko and Gennadiy Ostrenko.
The fee covers participation in all events of the programme - practical training, lectures and discussions with Ostrenko Brothers.
The official arrival day is January 24.
First group meeting is at 17:00.
The departure day is January 31 at 9:00.
10:00-12:00 - Practical training with Ostrenko Brothers.
14:00-17:00 - Practical training with Ostrenko Brothers.
19:30-21:00 - Creative diary: evening lectures, discussions and creation.
14:00-16:00 - Practical training with Ostrenko Brothers.
19:00 - IUGTE Conference opening and first meeting.
idyllic setting south of Graz, in Styria region, "Green Heart" of Austria.
Everything is organised on the same territory: creative space and full board accommodation, so that participants can concentrate on creation and communication without any distractions of the routine necessities.
IUGTE staff will be happy to help you with planning your itinerary!
Mr. Ostrenko assembled together. The tremendously talented group that I really hope I have the opportunity to work with again..."
"It was nice to practise the 'Throwing the Stone' etude and understand its context. For me the technical approach in learning the etude in a more detailed way was a good step forward and I feel I would like to still move forward in more etudes and get to know the forms of Biomechanics and how these relate to the various underlying principles".
"I continue thinking that the work of Biomechanics is very interesting and I will try to work applying it".
"What an enormous gift that "letting go" was! I carry the benefits of it with me still, into all my work and teaching that is to follow.
My time with IUGTE served to clarify and hone what I already know, it exposed me to new techniques and methodologies, and ultimately, it cast new light on the theatrical path ahead of me".
"I have never studied before the "throwing stone" of Meyerhold and it was nice learning a little peace more and more deeply every day studying Meyerhold´s main points and using this points in that sequence"
"This experience has re-awakened my desire to learn, to find projects and to improve my teaching and reminded me that a theatre artists training cannot end when they enter the professional world. In reality, that is when it should begin"


and show you YOU really are not alone in suffering!
completely different, and no matter how hard we try and put on a brave face its never how we used to feel.
I'm FINE. How many times a week do you hear yourself answering with that reply? Work colleagues, friends, family asking 'how are you?' My default reply: 'Fine thanks'. That one word to you sums up everything yet when answering, the person enquiring may not understand the full meaning of the word.
Frustrated. I'm frustrated that I have endometriosis. Frustrated that I find it so hard to do 'normal' daily things . If I have a busy day today then by tonight or tomorrow I know its going to catch up with me big time! The cramps will come, the pain wil increase. I cannot plan things. There's no exact pattern with endo. It can creep up on you out of the blue. Some days you know straight away it's going to be a bad day. Other days it can be so unexpected it will catch you out. You cannot predict which will be good or bad days. You either just have to say no or take your chances, say yes to a plan and hope you'll be ok. If you're not you end up cancelling last minute..again. That's frustrating. More so is the line 'but you look ok'. Yes, at the moment I may do. But you don't see me curled up on the floor unable to move because cramps are so strong. You don't see me crying and breaking down when the pain is so bad I don't know how I'm going to get through the next wave of pains. You also don't see that I've become a good actress. I may look ok to you but inside the pains are hurting so much I couldnt begin to describe them.
Neurotic. I feel like this alot. Before I was first diagnosed I had endless appointments with my doctor. I knew something was wrong, but my doctors at first didn't seem to agree. They said it was just IBS. To go home and change my diet. I knew it was something more but how could I prove it? All the tests and scans were done. Every single one came back clear. I did start to doubt myself. Was I really in that much pain? Yes I was, but endo can't be seen physically. Persistance is needed. If you think there is something wrong you need to voice it. More recently the neurotic feeling is creeping back up on me. I've decided to go for private healthcare and I have an appointment this friday with a specialist. However already im thinking what if he doesnt believe me? What if he thinks it's not as bad as i think it is? If im being stupid going private and should just wait a bit longer? Trying to reason with myself he won't think any of the above. He specialises in endo and has experience.
Emotional. So much so, some days I feel like an emotional wreck. I can go from being in good spirits to feeling so fed up and down in an instant. I can cry for no reason at all and find I can't stop. The mood swings are definately that. Swings. One minute your happy, the next you could scream and shout and scream again. The phrase an emotional rollercoaster is an understatement. It's very tiring.
So the next time someone answers that they are 'fine'...Please remember it is not as straight forward as you think. They know what fine means to them but it would be another exhausting avenue to go down to explain this to others...x"
& please check her page out!


kegemaran song Zayn has been featured on?
What's your kegemaran feature of Zayn?
Zayn Malik dyed his hair in the color merah jambu (and of course the bottom roots are menunjukkan in the color black.It is berkata that he did just in time for Valentine's hari to happen.His girlfriend Gigi Hadid didn't say anything about it yet.
Tell me what your thoughts in the komen-komen section and tell me whether anda think his new hair dye looks cool atau not.
I just heard that management didn't put ANY of Zayn's songs on the boys' new album Four. I feel so angry because that is totally unfair for Zayn. I haven't seen the lyrics to the song but I know that they must have been great. I'm not sure what anda guys think of this but I'm ticked off! Like come on! I just can't believe that this has happened. I mean I'm pretty sure Zayn has written a few songs before and they were pretty good. SO WHAT COULD BE SO WRONG WITH THESE SONGS!!!!!!!!! I just feel so bad for him. Sometimes I just want to strangle their management.
zayn i just cant think of life without you!! the reason im living today is you. i Cinta anda zayn.
u hv no idea how much i cried after anda got engaged 2 perrie edwards. it was such a happy hari for u, but the most sad hari for me. not just me but all ur female peminat followin.
I Cinta anda lebih THAN ANYTHIN IN THIS WORLD . I REALLY Cinta YOU!! ♥!!!!!!!!
IF anda HATE 1D IT DOES'NT MEAN TO BE MEAN TO THEM ON TWITTER atau Facebook atau EVEN INSTAGRAM AND THE PEOPLE WHO MAKE YouTube video ON HOW STUPID THEY ARE AND CRAP. THERE NOT STUPID anda KNOW. I'VE SEEN SO MANY VIDS OF HATE AND I'VE READ TONS OF HATE SO STOP PLZZ.
SO DIRECTIONERS IF anda WOULD PLZZ HAVE A hari TO SAY THERE NOT STUPID AND STUFF.
a question telah ditambah: What is my father's name?
TV tunjuk about Zayn Malik needs you!


text:
Le barrage de Guanyinyan est un barrage situé sur la rivière Jinsha (nom donné au cours supérieur du fleuve Yangzi Jiang), dans le Yunnan en Chine . Il est associé à une centrale hydroélectrique de .

Caractéristiques
Le barrage de Guanyinyan est situé sur la partie moyenne du cours de la rivière Jinsha, à une altitude de , en aval du barrage de Ludila.

Il s'agit d'un barrage-poids mixte : il comprend un segment de en béton, long de 817 mètres et haut de 159 mètres, occupant le fond de la vallée ; prolongé par un segment de en enrochement long de 341 mètres et haut de 71 mètres, construit sur la partie partie légèrement surélevée de la vallée. La longueur totale du barrage atteint , pour un volume de 9,36 millions de m3.

Le barrage de Guanyinyan a donné naissance à un lac de retenue d'un volume dépassant 2 km3. Le nombre de personnes déplacées est évalué à .

La centrale hydroélectrique comporte cinq turbines Francis de  chacune, dont trois fournies par Alstom, pour une puissance installée totalisant . La production électrique annuelle est estimée à .

Chronologie
La construction du barrage a débuté en 2008 et la rivière a été déviée en 2010. La première turbine est entrée en service le , les trois suivantes en 2015 et la sixième en 2016, marquant la mise en service complète de l'ouvrage.

Cascade hydroélectrique du Jinsha moyen
Le barrage de Liyuan est le huitième barrage d'une cascade hydroélectrique sur le Jinsha moyen, qui en comportera huit au total : Longpan, Liangjiaren, Liyuan, Ahai, Jinanqiao, , Ludila et Guanyinyan. Sur cette section de  entre Shigu et Panzhihua, le fleuve Yangzi Jiang chute de , offrant un potentiel hydroélectrique considérable.

Notes et références

Articles connexes
Liste des barrages hydroélectriques les plus puissants
Liste des plus hauts barrages
Hydroélectricité en Chine
Yangzi Jiang

Guanyinyan
Guanyinyan
Guanyinyan

redpajama_set_name: RedPajamaWikipedia


text:
R.J. Laforce
Join Date: May 01, 2012 • Last Entry Date: Apr 05, 2015 • Articles: 2007
R.J. LaForce is a programmer and Austin creative manager for the Alamo Drafthouse. He spent many years avoiding the real world by working at video stores, going to film school...twice, working on film and TV productions and anything else that involves movies. Whenever time away from watching movies allows him, he also writes for Badass Digest. So, really, he's still figuring out how to avoid the real world a little longer.
12 YEARS A HUSTLE: The Globes Define The Oscar Race
By R.J. Laforce, Jan 15, 2014
And then there were two...
INSIDE LLEWYN DAVIS Review: Assured, Minimalist Filmmaking
By R.J. Laforce, Nov 14, 2013
Who needs a plot in the hands of the Coen Brothers?
RUSHMORE And The Style And Substance Of Wes Anderson
By R.J. Laforce
WITHNAIL & I's Slow Burn To British Immortality
FRUITVALE STATION Review: You Will Know The Name Oscar Grant
By R.J. Laforce, Jul 26, 2013
The debut from 26-year-old Ryan Coogler is bold and immediate filmmaking.
Movie Review: BEFORE MIDNIGHT Is Emotionally Complex And Fully Satisfying
By R.J. Laforce, May 16, 2013
The latest film in Linklater's BEFORE trilogy is the new Drafthouse Recommends title.


Claus comes with 25 years of experience from the corporate world. He spend 7 year as the Managing Director for Luxottica South East Asia, Australia/New Zealand & South Pacific and before that he spend 18 years with Procter & Gamble in different leadership roles across Europe and Asia. He has also been active on different NGO boards over the last 6 years.
Claus comes with a passion and urgency to make real and sustainable change in the part of the world where its most needed.


Our strong and durable metal buildings are perfect for many agricultural applications including housing livestock, storing supplies or protecting farm machinery and equipment.
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Featuring rounded roof corners and horizontal metal panels, the Bent Bow style is our most affordable building option and works well for many agricultural applications. Choose your siding color and customize with front or back panels, windows, doors and more for the perfect building to meet your needs.
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Our metal barns can be endlessly configured for your specific needs and offer flexible sizing and customization options.


First, the predecessor to our reviewing court explained in In re Eynde, 480 F.2d 1364, 1370 (CCPA 1973), that facts constituting the state of the art are normally subject to the possibility of rational disagreement among reasonable people and are not amenable to the taking of official notice. Second, in In re Ahlert, 424 F.2d 1088, 1091 (CCPA 1970) the court held that assertions of technical fact in areas of esoteric technology must always be supported by citation to some reference work [admitted in evidence] and recognized as standard in the pertinent art. Moreover, the court held, facts officially noticed should not constitute the principal evidence upon which a rejection is based. Thus, mere assertions of fact, unsupported by evidence of record and an explanation, are not persuasive.


Front exhaust system with high performance catalyst.
From many years of developing the race exhausts for the Volkswagen Racing Cup, we have partnered with Milltek Sport to offer a more extreme 'Cup Edition' Front Exhaust downpipe and catalyst for the MQB-platform cars with 2.0 TSI engines.
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We supply exhaust systems for various applications. For a system specific to your car please call us.
Our OEM+ Stage 3 upgrade offers a complete, turn-key package that is entirely usable on a daily-driven car yet offers devasting performance just one squeeze of the throttle away.


text:
Note with threat against BBPB HS found
BEN BOLT - Officials at Ben Bolt-Palito Blanco High School were on alert after the discovery of a hand-written note on Wednesday.
According to the school district, the note was found in the morning that indicated that a violent act was going to take place at the high school on Thursday, Nov. 14.
Officers with the Jim Wells County Sheriff's Office and the Department of Public Safety immediately. An investigation is currently underway along with a heightened safety and security plan, according to the district.
Classes will resume on Thursday, but with an increase on police presence around the school and campus throughout the day.
All threats to the school or students are taken seriously and investigated thoroughly.
School officials encourage parents to talk with their children about the seriousness of threats.
Anyone with information about the incident is urged to call police.
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Nueces County Record Star
City of Alice
Alice ISD
Beck & Masten Buick
Alice Echo News-Journal ~ 405 East Main Street, Alice, TX 78332 ~ Do Not Sell My Personal Information ~ Cookie Policy ~ Do Not Sell My Personal Information ~ Privacy Policy ~ Terms Of Service ~ Your California Privacy Rights / Privacy Policy
The SouthTexas Real Estate
Alice Magazine
Election Day 2018
South Texas - Buena Gente


Thank you for selecting the Life Vessel Denver of Denver, CO. Whether your decision to visit our Strategies for Healing, Inc. offices is based on resolving a specific condition or simply addressing preventative wellness as an approach to good health, our objective is to assist you in reaching your health-related goals.
Please review the attached checklist in preparation for your visit. Should you have any questions or if we can be of assistance in any way, please do not hesitate to contact us.
Please read all the material on this page.
Please complete all forms and make arrangements (email, fax, mail, etc.) for them to arrive at our office prior to your first visit.
Collect and send all pertinent lab data related to your condition. Please include blood work, scans, radiology or any other test results.
Please reschedule any chiropractic, massage, acupuncture, or any other "energy work" planned for within three weeks following your visit.
Commit to drinking a minimum of one gallon of water a day (16 cups / 128 oz.) starting the day before your first Life Vessel session and continuing for the next 21 days. This is a part of the treatment and is a requirement. We will be unable to continue sessions unless you are prepared to do this.
Please refrain from eating one (1) to two (2) hours prior to your first Life Vessel visit. Drinking a modest amount of water prior to your first visit is okay.
Please dress comfortably and casually (loose-fitting clothing and minimal jewelry are highly suggested. Sports bras or underwire bras are not recommended for women).
Please do not wear any colognes, perfumes, or fragrant lotions the day of your treatment.
Please turn off your cell phone prior to arriving at the Strategies for Healing and Life Vessel Denver offices.
Please understand that your past habit patterns could well be impacting your present condition. This may necessitate a re-evaluation of your lifestyle, whether it is diet, exercise, food choices or habitat. Please be prepared to discuss any recommended adjustments that may be required to regain your optimum health.


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text:
De waternimf in de vijver of De nimf in de vijver is een sprookje uit Kinder- und Hausmärchen met volgnummer KHM181, opgetekend door de gebroeders Grimm. De oorspronkelijke naam is Die Nixe im Teich.

Het verhaal

Een molenaar en zijn vrouw worden elk jaar rijker en zijn gelukkig, maar op een dag keert het lot en ze verliezen steeds meer bezittingen. De molenaar vindt geen rust in bed. Hij ziet op een ochtend een mooie vrouw uit het water oprijzen als hij over de molendam loopt. Haar haren bedekken haar lichaam en hij weet dat het de nimf van de vijver is. Hij weet niet of hij moet weglopen of moet blijven staan en hij hoort haar mooie stem. Ze vraagt waarom hij zo bedroefd is.

De molenaar vertelt wat er is gebeurd en de nimf belooft dat hij rijker dan ooit zal worden in ruil voor het eerste wat in zijn huis geboren wordt. De molenaar denkt aan een hond of kat en belooft de nimf wat ze wil. Hij gaat naar huis en de meid vertelt dat zijn vrouw bevallen is van een jongetje. Hij vertelt zijn vrouw over de belofte en hij vraagt zich af wat hij aan geluk en rijkdom heeft als hij zijn kind moet afstaan. De familie weet geen raad en het geluk keert in huis terug, maar de molenaar kan niet genieten van de luxe. Hij laat het jongetje niet in de buurt van het water komen en hij waarschuwt over een hand die hem grijpen zal.

De jongen wordt een jongeman en komt bij een jager in de leer. De heer van het dorp neemt hem na een tijd als jager in dienst en hij krijgt een klein huisje en trouwt een mooie vrouw. Ze houden van elkaar en de jager schiet op een dag een ree, maar merkt niet dat hij bij de vijver is. Hij ontweit het dier en wil zijn handen in het water wassen, maar dan komt de nimf naar boven. Ze slaat haar natte armen om hem heen en trekt hem mee naar beneden. De vrouw wordt bang en gaat op zoek, ze ziet zijn weitas bij de oever. Ze roept naar haar man en de nimf, maar er komt geen antwoord en de waterspiegel blijft kalm. De vrouw blijft bij de vijver en ze droomt over grote rotsblokken en dorens en ranken, regen en wind. Ze ziet een groene wei vol bonte bloemen en een hutje met een oude vrouw met wit haar. Ze wordt wakker en ze beklimt de berg en alles is zoals ze droomde.

De vrouw ontvangt haar en geeft een gouden kam, waarmee ze haar zwarte haren moet kammen tijdens volle maan. Ze moet de kam op de oever laten liggen en de vrouw ziet dat een golf de gouden kam meeneemt. Het hoofd van de jager komt boven de waterspiegel en hij kijkt bedroefd naar zijn vrouw. Een tweede golf laat het gezicht verdwijnen en de vrouw gaat naar de hut na een nieuwe droom. De oude vrouw geeft een fluit en na een lied moet deze op de oever worden gelegd. De vrouw maakt muziek en ziet hoe een golf de fluit meeneemt. Het hoofd en de bovenste helft van het lichaam van de jager komen uit het water, maar een golf trekt hem naar beneden. De vrouw droomt opnieuw over de oude vrouw en ze gaat opnieuw naar de hut. De vrouw vertelt dat ze met een spinnewiel aan de oever moet zitten en ze moet de spoel vol spinnen. De vrouw ziet hoe een golf het spinnewiel meeneemt en ze ziet haar man en hij springt aan land. Hij pakt de hand van zijn vrouw en ze rennen weg, waarna de hele vijver over het land stroomt.

De vrouw roept de oude vrouw om hulp en zij en haar man veranderen in een kikker en een pad. Ze worden uiteen gesleurd en als het water zakt, krijgen ze hun menselijke gedaante terug. Ze weten niet waar ze zijn en ze gaan schapen hoeden. Na jaren komen ze elkaar weer tegen, maar ze herkennen elkaar niet in het dal. Ze blijven bij elkaar en zijn niet meer eenzaam. Als het volle maan is en de schapen rusten, pakt de herder zijn fluit en speelt een lied. De herderin huilt en zegt dat ze het lied ook speelde en het hoofd van haar man zag in een ver verleden. Dan herkennen ze elkaar en ze kussen, niemand hoeft te vragen of ze gelukkig zijn.

Achtergronden bij het sprookje
Het sprookje komt uit Opper-Lausitz en was opgetekend in Zeitschrift für deutsches Alterthum (1842).
Het is een echt watersprookje met een waternimf (Nixe, een pad, een kikker en een overstroming.
Het sprookje heeft overeenkomsten met De waternimf (KHM79).
De overhaaste belofte komt ook voor in het Bijbelverhaal over Jefta (Richteren 11), Raponsje (KHM12), Het meisje zonder handen (KHM31), De zingende springende leeuwerik (KHM88), De koning van de gouden berg (KHM92), Hans-mijn-egel (KHM108), De drie groene twijgen (KHM206) en in Het meisje zonder handen uit Sprookjes uit de Lage landen. Ook in Het kind van Maria (KHM3) wordt een meisje weggegeven.
Drie toverdingen komen ook voor in Tafeltje dek je, ezeltje strek je en knuppel uit de zak (KHM36), De ransel, het hoedje en het hoorntje (KHM54), De gouden gans (KHM64), De koning van de gouden berg (KHM92), De raaf (KHM93), De jood in de doornstruik (KHM110), De ijzeren kachel (KHM127) en Het klosje, de schietspoel en de naald (KHM188).
De molenaar als vader, zie ook Het meisje zonder handen (KHM31), De roversbruidegom (KHM40), Repelsteeltje (KHM55) en De arme molenaarsknecht en het katje (KHM106).
De behulpzame oude vrouw komt in vele sprookjes voor, bijvoorbeeld in De twaalf broeders (KHM9), De duivel met de drie gouden haren (KHM29), De roversbruidegom (KHM40), De drie vogeltjes (KHM96), De zoete pap (KHM103), De groente-ezel (KHM122), De duivel en zijn grootmoeder (KHM125), De stukgedanste schoentjes (KHM133), De ganzenhoedster aan de bron (KHM179), De ware bruid (KHM186), Het klosje, de schietspoel en de naald (KHM188) en De laars van buffelleer (KHM199).
 Gedaanteverwisseling, zie ook metamorfose (mythologie).
Vergelijk Jorinde en Joringel (KH69), Jonkvrouw Maleen (KHM111) en IJzerhans (KHM136).
De jacht op het ree komt ook voor in De twee broers (KHM60), De goudkinderen (KHM85) en De twee koningskinderen (KHM113).
Verlossing door spinnen komt ook voor in De zes zwanen (KHM49) en het verdwenen Prinz Schwan. Denk ook aan de draad van Ariadne die verlossing uit het labyrint van de Minotaurus kon bieden.
Voorspoed kan omslaan in tegenspoed, zie zegen en vloek, het Rad van Fortuin en Vrouwe Fortuna.
Een gedaanteverwisseling op de vlucht komt ook voor in Vondevogel (KHM51), Vrijer Roland (KHM56) en De stukgedanste schoentjes (KHM133).
Een waternimf wordt ook wel watergeest genoemd, zie ook geest. Denk ook aan de zeemeermin of sirene (halfgodin).
Vergelijk Watramama, de vorstin van rivieren.

Sprookje van de gebroeders Grimm


text:
\section{Introduction}

Homography estimation is essential for inverse perspective mapping (IPM) \cite{jeong2016adaptive} and planar parallax estimation \cite{irani1996parallax} where a reference plane is referred, which further helps lane detection, bird's-eye view (BEV) generation and other vision tasks in autonomous driving.

Traditional homography estimation methods compute sparse feature correspondences between subsequent frames and apply the RANSAC algorithm ~\cite{fischler1981random}, which requires sufficiently large ego-motion. Furthermore, the effectiveness of such methods relies heavily on high quality feature correspondences, making it challenging in autonomous driving scenarios since the road surface is usually weakly-textured, occluded, or with repetitive patterns.

CNN-based methods treat homography estimation as a regression problem via the 4-point parameterization \cite{detone2016deep,nguyen2018unsupervised, zhang2019content}. By leveraging high level context features, these methods often outperform the traditional methods on challenging cases mentioned above. The drawback is that even though ego-motion and planar geometry can be recovered via homography matrix decomposition, such methods cannot provide true scale desired for autonomous driving.

Another branch of methods calculate homogrpahy matrix explicitly according to Eqn.~\ref{homography} which use ego-motion, ground plane and camera intrinsic parameters. While camera intrinsic parameters can be obtained via offline calibration, accurate ego-motion and ground plane estimation remains a challenge problem.

To estimate ego-motion, Visual Odometry (VO) or Structure from Motion (SFM) are commonly utilized \cite{hartley2003multiple}. Sensors fusion with filter-based \cite{davison2007monoslam} or optimize-based frameworks \cite{klein2007parallel} can increase the accuracy and robustness. These methods usually requires large ego-motion as well. Recently, CNN-based methods have gained popularity. The supervised methods \cite{kendall2015posenet, li2017indoor, clark2017vidloc} regressed 6D pose directly, while the unsupervised methods \cite{monodepth2, godard2017unsupervised, li2018undeepvo} estimate pose and depth to construct supervisory signals via new view synthesis \cite{zhou2017unsupervised}. These methods can obtain accurate ego-motion even with small motion parallax, however they do not guarantee accurate homography estimation.

Similar to ego-motion estimation, ground plane also can be estimated from either geometry or learning based methods \cite{mcdaniel2010ground, se2002ground, man2019groundnet, xiong2020joint}. Geometry based methods obtain plane geometry by directly fitting a plane to the 3D points acquired from depth sensors or multi-view stereo. When only a single image is available, the ground normal (the plane coefficients) can be recovered by detecting vanishing points and the horizon line \cite{hartley2003multiple}. Recently, CNN-based methods are proposed to regress ground normal \cite{bansal2017pixelnet, qi2018geonet} from a single input image as well. Up to now, the performance of CNN-based methods are inferior to geometry based methods.

Our method also explicitly computes homography using ground plane and ego-motion. Differentiating from the aforementioned work, we propose to simultaneously optimize all these objectives in one network. In addition, we observe that adding depth estimation brings further improvement. The resulting multi-task network predicts depth, ego-motion, and ground plane at the same time. The depth and ego-motion sub-networks constitute learning-based SFM \cite{zhou2017unsupervised}, while the ego-motion and ground plane derives the ground homography matrix. The architecture of the network is demonstrated in Figure \ref{fig:network}. The entire network can be trained in a weakly-supervised manner, i.e., only requiring road segmentation from any off-the-shelf semantic segmention model to limit photometric loss to the road region, while completely eliminating the need for expensive 3D groundtruth.

Our main contributions are summarized as follows:
\begin{itemize}
    \item We propose a novel multi-task learning framework which can solve SFM (ego-motion and depth) and ground plane homography simultaneously.

    \item We design the photometric loss, homography loss and depth-smoothness loss in a way such that the sub-networks provide supervisory signals for one another, hence the training can be done without any groundtruth other than a road segmenter.
    \item We show that joint learning can improve performance of all sub-tasks over existing methods through experiments on the KITTI benchmark dataset \cite{geiger2012we}.

\end{itemize}

\begin{figure*}[t]
\begin{center}

   \includegraphics[width=1.0\linewidth]{network5.pdf}
\end{center}
   \caption{The overview of our network architecture. Our network consists of a Depth-CNN, a Pose-CNN and a Ground-CNN. The input are two consecutive images while the output are depth, ego-motion, ground plane as well as road homography. The output depth along with the ego-motion can be used to reconstruct the source image. While the homography and ego-motion are used to reconstruct the road surface. The road mask are provided by an off-the-shelf segmenter.}
\label{fig:network}
\end{figure*}

\section{Related Work}
In this section, we introduce the works most relevant to our method including homography estimation, visual odometry and ground plane estimation.

\subsection{Homography Estimation}
Homography describes the corresponding relationship of the points on the same plane imaged in two views. An increasing number of works focus on homography estimation to support other vision tasks, such as image stitching and IPM. We roughly classify existing methods into two categories: implicit methods and explicit methods.

Traditional implicit methods utilize geometry constraint to estimate homogrpahy. The most common idea is to first conduct keypoints detection and matching, and then find the optimal homography via RANSAC outlier rejection~\cite{fischler1981random}. This kind of methods is quite effective and robust when the features are of high quality. Nonetheless, the performance may degrade dramatically when the detected keypoints are insufficient or distribute unevenly, which is common phenomenon in driving scenes. Recently, inspired by the success of deep convolution neural network (CNN) in computer vision, deep homography estimation methods become prevalent \cite{detone2016deep,nguyen2018unsupervised, zhang2019content,le2020deep}. These methods directly regress the coordinates offset of specified 4 points~\cite{detone2016deep} according to the 4-points parameter estimation. However, a great improvement is demanded for the deep homography to be superior to traditional methods. On the one hand, implicit methods estimate homography directly from a image pair ignoring the true motion between two views. On the other hand the resulted homography may not be guaranteed corresponding to the road plane. The above two reasons make implicit methods unsuitable for applications where a reference plane is required.

Explicit methods \cite{hartley2003multiple,xiong2020joint} usually translate the homography estimation problem into two sub-problems: ego-motion and ground plane estimation, assuming the camera intrinsic parameters are known previously. Hartley et.al \cite{hartley2003multiple} first used the normal vectors of the coplanar points and ego-motion to construct a homography. Our method is also belong to the explicit methods, but we implement it via CNNs

\subsection{Structure From Motion}

SFM has been a research hotspot for decades. Existing methods can be categorized into geometry-based and learning-based methods. Geometry-based methods optimize ego-motion by minimizing reprojection errors or photometric errors \cite{mur2015orb} between images. Some methods \cite{engel2017direct, engel2014lsd}achieve impressive performance with careful parameter tuning, but they are still prone to scale drift as well as scale ambiguity.

Recently deep learning based methods are popular for visual odometry estimation. The DeepVO method \cite{wang2017deepvo} is the first learning based method which utilizes a recurrent neural network to obtain ego-motion. Due to the use of temporal constraint, the results achieve good accuracy and smoothness. However, the dependence on labeled data hinders it's application to practice. To solve this problem, unsupervised method are proposed \cite{zhou2017unsupervised,monodepth2,xue2020toward}. The SFM-Learner proposed in \cite{zhou2017unsupervised} individually designed depth network and pose network and incorporated depth and ego-motion into loss function to generate supervisal signals. Chen et al. \cite{chen2019self} introduced optical flow into this framework aiming at reducing the impact of dynamic regions on ego-motion estimation. As the photometric loss over optical flow decrease much more easily than over depth and ego-motion, the backward gradient is dominated by optical flow. Gordon et al.~\cite{2019Depth} replaced optical flow with residual flow to strengthen the depth and ego-motion learning. Although these methods achieve a great success, they cannot recover the metric depth and ego-motion.

Some methods \cite{sucar2017probabilistic,xue2020toward,roussel2019monocular}
also try to recover real scale of the scene by leveraging prior information such as height of the camera, etc.

\subsection{Ground Plane Estimation}
Ground plane estimation methods can also be divided into geometry-based methods and learning-based methods. Geometry-based methods usually calculate the plane through a robust model fitting algorithm like RANSAC. McDaniel et al. \cite{mcdaniel2010ground} used the 3D point cloud from LIDAR to identify the ground plane. \cite{se2002ground} estimated the ground plane by using the 3D point cloud generated from stereo disparity. The accuracy of geometry-based method heavily depend on the quality of depth information.

Learning-based methods attempt to estimate the ground plane either directly or indirectly from other related tasks. \cite{haines2012detecting} learn a classifier to distinguish local planar image patches and their orientations. The Man et al. \cite{man2019groundnet} proposed the GroundNet to first combine convolutional neural network and geometric consistency about depth and normal for ground plane estimation. Similarly, our method also leverage a network to predict the ground plane.

\section{Method}

In this section, we firstly introduce the whole framework of our method including three networks and a novel homography layer. After that we give the explanation of the unsupervised training loss. Finally, we show that how our method can recover the real scale of the road scene.

Suppose there are two successive frames at time $t$ denoted as $I_{t-1}$ and $I_{t}$ respectively, the depth map corresponding to $I_{t}$ is denoted as $D_{t}$. The ego-motion between $I_{t-1}$ and $I_{t}$ is a rigid transform $\mathbf{T}_{t\to{t-1}}\in\mathbb{R}^{4\times 4}$. The ground plane in $t$-$th$ frame is parameterized by $\mathbf{N}_t$ and $h_t$, where $\mathbf{N}_t$ is a normal vector with two degrees of freedom. $h_t$ is the signed distance from the coordinate origin to the plane, which can be identical to the mounting height of camera.

\subsection{Network}
\textbf{CNN-SFM}  We use a Depth-CNN and a Pose-CNN similar to \cite{monodepth2}. The Pose-CNN takes two frames $I_{t-1}$ and $I_{t}$ as input and estimates the ego-motion $\mathbf{T}_{t\to{t-1}}$, while the Depth-CNN only takes one single frame $I_{t}$ as input and regresses depth map $D_t$. The rotation of $\mathbf{T}_{t\to{t-1}}$ is represented via angle-axis vector donated as $\alpha_t$, $\beta_t$, $\gamma_t$.

\textbf{Ground Plane Estimation Via Deep Correction}
In our method, we adopt a learning-based manner to estimate the ground plane. Specifically, a Ground-CNN is designed to estimate the ground plane  $\mathbf{N}_t\in\mathbb{R}^{3\times1}$ and the mounting height of the camera $h_t$ to the ground plane. The ground plane in $t$-th frame can be represented as
\begin{equation} \label{palne}
    \mathbf{N}_t^T \mathbf{P} + h_t = 0,
\end{equation}
where $\mathbf{P}\in\mathbb{R}^{3\times1}$ is the 3D points of the road surface in the $t$-$th$ frame.

Observing that the ground planes in driving scenes vary smoothly in most cases, we apply a residual block to learn the offset of ground plane parameters. Specifically, we estimate the variation of the normal and height of the ground plane instead of themselves since residuals are usually more easily to learn. This process can be formulated as
\begin{equation} \label{normal-variation}
    \mathbf{N}_t = \delta\mathbf{R}_t\Bar{\mathbf{N}} ,
\end{equation}
\begin{equation} \label{height-variation}
    h_t = \delta h_t+\Bar{h} ,
\end{equation}
where $\Bar{\mathbf{N}}$ and $\Bar{h}$ can be obtained from initial calibration, and then keep unchanged. We ignore the roll component of $\delta\mathbf{R}_t$, since it would have no impact on the normal estimation.
\begin{equation} \label{height-variation}
  \delta\mathbf{R}_t = \mathbf{R}(\delta r_t)\mathbf{R}(\delta s_t ),
\end{equation}
where $\delta r_t$, $\delta s_t$ and $\delta h_t$ are the outputs of the Ground-CNN.

The backbone of our Ground-CNN is ResNet-18 \cite{he2016deep}, which takes $I_t$ as input and outputs a 3-dim vector [$\delta r_t$, $\delta s_t$, $\delta h_t$] defined above. Compared to \cite{se2002ground} regressing the normal of each pixels, we simply regress the ground plane normal by leveraging the consistency between the normal and depth to increase the robustness.

\textbf{Homography Layer} We propose a simple but effective homography layer to regress homograpy matrix. The input of the layer are ego-motion ($\mathbf{R}_{t\to{t-1}}$ and $\mathbf{t}_{t\to{t-1}}$), ground plane ($\mathbf{N}_t$ and $h_t$) and the output is the homogrpahy matrix $\mathbf{H}_{t\to{t-1}}\in\mathbb{R}^{3\times3}$.
According to the definition of homography with respect to ego-motion and a reference plane, we can get the road homography as follows:
\begin{equation}\label{homography}
    \mathbf{H}_{t\to{t-1}} = \mathbf{K}(\mathbf{R}_{t\to{t-1}} - \cfrac{\mathbf{t}_{t\to{t-1}}  \mathbf{N}_t^T}{h_t})\mathbf{K}^{-1},
\end{equation}
where $\mathbf{K}\in\mathbb{R}^{3\times3}$ is the intrinsic matrix of the camera, which is assumed to be calibrated in advance. The derivatives respect to ego-motion and ground plane in the  back-propagation can be derived as following (the subscripts are omitted for simplicity)
\begin{equation}
\begin{split}
    \cfrac{\partial(\mathbf{Hx})}{\partial \mathbf{R}} = -(\mathbf{Rx})^{\wedge},
\end{split}
\end{equation}

\begin{equation}
\begin{split}
    \cfrac{\partial(\mathbf{Hx})}{\partial \mathbf{t}}  =  - \cfrac{\mathbf{N x}}{h},
\end{split}
\end{equation}

\begin{equation}
\begin{split}
    \cfrac{\partial(\mathbf{Hx})}{\partial h} = \cfrac{\mathbf{KtN^TK}^{-1}\mathbf{x}}{h^2},
\end{split}
\end{equation}

\begin{equation}
\begin{split}
    \cfrac{\partial(\mathbf{Hx})}{\partial \mathbf{N}}  = -\cfrac{\mathbf{t x}}{h},
\end{split}
\end{equation}
where, $\mathbf{x}$ represents the homogeneous image coordinates of a pixel and $(\cdot)^{\wedge}$ means the corresponding skew matrix of a 3-dim vector. Note that there are no parameters to be updated in the homogrpahy layer. Since the homogrpahy layer is differentiable, in training phrase the derivatives will be propagated. In the inference phrase, the homography layer output the homography matrix.

\begin{table*}
    \begin{center}
        \begin{tabular}{|c|r|r|r|r|}
            \hline
            \multirow{2}*{Method} &
            \multicolumn{2}{|c|}{sequence 09} &
            \multicolumn{2}{|c|}{sequence 10} \\
            \cline{2-5}
            & $ t_{err}(\%)$ & $ r_{err}(^{\circ}/100m)$ & $ t_{err}(\%)$ & $ r_{err}(^{\circ}/100m)$ \\ \hline
            ORB-VO  & 14.00 & 3.06 & 13.23 & 5.08 \\ \hline
            Zhou et al.\cite{zhou2017unsupervised} & 17.84 & 6.78 & 37.91 & 17.78\\
            Monodepth2\cite{monodepth2}  & 14.88 & 3.43 & 11.83 & 4.93  \\
            Ours & \textbf{5.11} & \textbf{2.12} & \textbf{5.19} & \textbf{2.62} \\
            \hline
        \end{tabular}
    \end{center}
    \caption{Evaluation results of visual odometry on KITTI test sequences. $t_{err}$ and $r_{err}$ represent Relative Translation Error (RTE) and Relative Rotation Error (RRE) respectively. The best results are reported in bold.}
    \label{tab:p_est}
\end{table*}

\subsection{Loss Function}
In our method, the framework is trained in an unsupervised manner. The training loss is composed of three components: photometric loss, homography loss and the scale loss.

\textbf{Photometric Loss}
The photometric loss is commonly used in unsupervised learning based visual odometry estimation methods \cite{monodepth2}. It measures the difference between target image and the reconstructed image from source image through the outputs of the network. Given ego-motion $\mathbf{R}_{t\to{t-1}}$ and the depth map $D_t$ of frame $I_t$, we can find a correspondence between two images through
\begin{equation}\label{eqn-reprojection}
    \mathbf{p}_{t-1} \backsim \mathbf{K}(\mathbf{R}_{t\to{t-1}}D_t(\mathbf{p}_t)\mathbf{K}^{-1}\mathbf{p}_t	+ \mathbf{t}_{t\to{t-1}}),
\end{equation}
where $\mathbf{p}_{t-1}$ and $\mathbf{p}_{t}$ are corresponding pixels in frames $I_{t-1}$ and $I_t$ respectively, and $D_t(\mathbf{p}_t)$ represents the depth of $\mathbf{p}_t$. Thus, frame $I_t$ can be reconstructed as
\begin{equation}
    I_{t'}[\mathbf{p}_{t}] = I_{t-1} \langle \mathbf{p}_{t-1}	\rangle ,
\end{equation}
where $I_{t'}[\mathbf{p}_{t-1}]$ are color values at position $\mathbf{p}_{t-1}$, and $\langle \rangle$ is a bilinear sampling operator.

Similar to \cite{zhao2016loss, godard2017unsupervised}, we also use a robust photometric error combining structural similarity (SSIM) \cite{wang2004image} and L1 norm between two images which is given by
\begin{equation} \label{photo-loss}
    E_p(I_t, I_{t'}) = \alpha \cfrac{1-SSIM(I_t, I_{t'})}{2} + (1 - \alpha) ||I_t - I_{t'}||,
\end{equation}
where $\alpha$ is a hyper-parameter.

In addition, we rely on smooth depth assumption whereby we apply edge-aware regularization to the discontinuities in the predicted depth map $D_t$ by minimizing
\begin{equation}\label{smooth-loss}
    E_s(D_t) = |\partial_x d^*_t| e^{-\partial_x|I_t|}+|\partial_y d^*_t| e^{-\partial_y|I_t|},
\end{equation}
where ${\overline{d_t}}$ is the mean-normalized depth. $\partial_x(\cdot)$ and $\partial_y(\cdot)$ represent the gradient operator in horizontal and vertical direction respectively.

{\bf Homography Loss} Given an image $I_t$, we use a road map $M_t$ to remove the non-road region from the color image by
\begin{equation}\label{road-seg}
   \tilde{I}_t = M_t\odot I_t,
\end{equation}
where $M_t$ is a binary mask which can be obtained from a semantic segmentation model.

If two corresponding points $\mathbf{p}_{t-1}$ and $\mathbf{p}_{t}$ are located on the assumed road surface, they will satisfy
\begin{equation}
   \mathbf{p}_{t-1} = \mathbf{H}_{t\to{t-1}} \mathbf{p}_{t}.
\end{equation}
Similar to photometric error, we can reconstruct the road region by using
\begin{equation}\label{homo-warp}
   \tilde{I}_{t'}^h[\mathbf{p}_t] = \tilde{I}_{t-1}\langle\mathbf{p}_{t-1}\rangle,
\end{equation}
where $\tilde{I}_{t'}^h$ represents image warped by a homography.
Combining Eqn.\ref{road-seg} and Eqn.\ref{homo-warp} we get the homography loss as
\begin{equation}\label{homo-loss}
   E_h(I_t, I_{t'}) = |\tilde{I}_{t'}^h - \tilde{I}_{t}|,
\end{equation}
where $|\cdot|$ is the L1 loss.

\textbf{Scale Loss} Absolute scale of the scene is hard to estimate for monocular visual odometry. To solve this problem, we use the camera height $h_c$ to decide the absolute scale of the scene. $h_c$ can be reliably accquired when the road plane and camera center are obtained. To keep the scale between SFM and homography consistent, we dynamically adjust the scale of the estimated depth. We compute the relative scale between the calibrated $h_c$ and the predicted $h_t$ as follows
\begin{equation}\label{depth-scale}
    s = \cfrac{h_c}{h_t},
\end{equation}
Base on Eqn.~\ref{depth-scale}, the predicted depth can be adjusted by using
\begin{equation}
    \hat{D}_{t} = sD_t.
\end{equation}
Then, $\hat{D}_{t}$ is substituted to compute all the losses defined above.

\textbf{Total loss} Combining Eqns.~\ref{photo-loss}, \ref{smooth-loss} and \ref{homo-loss}, the total loss between frame $I_{t-1}$ and $t_{t}$ is defined as
\begin{equation}
    E = \mu E_p + \lambda E_s + \xi E_h,
\end{equation}
where $\mu$, $\lambda$ and $\xi$ are balancing factors.

\begin{figure}[t]
\begin{center}

   \includegraphics[width=1.0\linewidth]{traj_09.pdf}
   \includegraphics[width=1.0\linewidth]{traj_10.pdf}
\end{center}
   \caption{Trajectories of different methods on KITTI odometry test sequences. The top and bottom images show the results of sequence 09 and 10 respectively. Different colors represent the results of different methods}
\label{fig:pose}
\end{figure}

\begin{table*}
    \begin{center}
        \begin{tabular}{|c|c|r|r|r|r|r|r|r|}
            \hline
            \multirow{2}*{Method} &
            \multirow{2}*{Scale Factor} &
            \multicolumn{4}{|c|}{Lower is better} &
            \multicolumn{3}{|c|}{Higher is better} \\
            \cline{3-9}
            && Abs Rel & Sq Rel & RMSE & RMSE log & $\delta < 1.25$ & $\delta < 1.25$ & $\delta < 1.25$ \\ \hline \hline
            Zhou et al.\cite{zhou2017unsupervised} &  GT &  0.183 & 1.595 & 6.709 & 0.270 & 0.734 & 0.902 & 0.959 \\
            Yang et al. \cite{yang2017unsupervised} & GT & 0.182 & 1.481 & 6.501 & 0.267 & 0.725 & 0.906 & 0.963\\
            Mahjourian et al.\cite{mahjourian2018unsupervised} & GT & 0.163 & 1.240 & 6.220 & 0.250 & 0.762 & 0.916 & 0.968\\
            DDVO \cite{wang2018learning} & GT & 0.151 & 1.257 & 5.583 & 0.228 & 0.810 & 0.936 & 0.974\\
            DF-Net \cite{zou2018df} & GT & 0.150 & 1.124 & 5.507 & 0.223 & 0.806 & 0.933 & 0.973\\
            GeoNet \cite{yin2018geonet} & GT & 0.149 & 1.060 & 5.567 & 0.226 & 0.796 & 0.935 & 0.975\\
            EPC++ \cite{luo2019every} & GT & 0.141 & 1.029 & 5.350 & 0.216 & 0.816 & 0.941 & 0.976\\
            Struct2Depth \cite{casser2019depth} & GT & 0.141 & 1.026 & 5.291 & 0.215 & 0.816 & 0.945 & 0.979\\
            CC  \cite{ranjan2019competitive} & GT & 0.139 & 1.032 & 5.199 & 0.213 & 0.827 & 0.943 & 0.977\\
            Bian et al. \cite{bian2019unsupervised} & GT & 0.128 & 1.047 & 5.234 & 0.208 & 0.846 & 0.947 & 0.976\\
            Monodepth2 \cite{monodepth2} & GT & 0.115 & 0.903 & 4.863 & 0.193 & 0.877 & 0.959 & 0.981\\

            Ours  & GT & \bf{0.111}  &   0.894  &   \bf{4.779}  &   \bf{0.189}  &   \bf{0.883}  &   \bf{0.960}  &   \bf{0.981}  \\
            \hline
            DNet\cite{xue2020toward}  & DGC & 0.118 & 0.925 & 4.918  & 0.199 & 0.862 &  0.953 & 0.979\\
            Ours  & H &0.128  &   0.936  &   5.063  &   0.214  &   0.847  &   0.951  &   0.978  \\
            \hline
        \end{tabular}
    \end{center}
    \caption{Depth evaluation results on the KITTI Eigen split \cite{eigen2014depth}. ``GT'' standards that results are usually reported using the per-image median ground truth scaling strategy introduced by ~\cite{zhou2017unsupervised}. ``DGC'' standards a method \cite{xue2020toward} to filter out the ground area and then calculate the median value of the camera height and ``H'' standards the predicted camera height by our method. The best results are reported in bold.}
    \label{tab:d_est}
\end{table*}

\section{Experiments}

We evaluate our methods from three aspects separately: depth and ego-motion (visual odometry) evaluation, homography, and ground normal evaluation. Comparative experiments with \cite{monodepth2} and \cite{mur2015orb} are conducted to show the effectiveness of our method.

All the experiments are carried out on the KITTI benchmark which captured from various challenging scenes, e.g. highway, urban, and rural areas. Ground truth for visual odometry and depth evaluation are already provided. To the best of our knowledge, we are the first to evaluate homography and ground normal on KITTI dataset.

To evaluate the homography estimation accuracy, we construct a homography validation dataset via feature based method, which is generated from the sequence 09 and 10 in KITTI's Odometry benchmark. Specifically, we first extract and match keypoints in the road region. After that we estimate the homogrpahy via 8-point algorithm and RANSAC algorithm \cite{fischler1981random}. To guarantee the reliability of the correspondence, we set the inlier threshold as 0.5 pixels. Finally, image pairs with inlier correspondences greater than 50 and keypoints evenly distributed will be selected to constitute the validation dataset. Similar to existing methods~\cite{ zhang2019content,le2020deep} the reprojection errors of the correspondences are utilized as a metric to evaluate the homography accuracy.

We also generate ground-truth road plane for ground normal evaluation through a simple method. We first extract depth of the road region by leveraging the segmentation mask and then convert the depth to 3D points via inverse projection \cite{hartley2003multiple}. Following, we compute road plane by using the RANSAC \cite{fischler1981random} as well. Similar to homography, we discard images with a inlier ratio less than 0.6 which means the road surface is possible to be non-planar. The generated ground-truth road plane is believed to be reliable benifit from accuracy of the groundtruth depth.

\subsection{Implementation Details}
The whole framework is composed of three sub-networks: Depth-CNN, Pose-CNN, and Ground-CNN. The configuration of Depth-CNN and Pose-CNN has the same setting as in \cite{monodepth2}. The hyperparameters $\mu$, $\lambda$, $\xi$ and $\alpha$ are set to 1.0, 0.001, 0.1 and 0.85 in all our experiments.
We train our model on NVIDIA GeForce GTX TITAN X for 20 epochs with batch size 8 and initial learning rate 0.0001. The Adam optimizer \cite{kingma2014adam} is used for training.

\subsection{Depth and Visual Odometry Evaluation}
We follow KITTI benchmarks to perform quantitative depth and VO evaluation for our method. The proposed method is compared with both learning-based and traditional monocular methods. Among which Monodepth2 ~\cite{monodepth2} is the state-of-the-art learning-based method trained in unsupervised manner with monocular configuration, while the ORB-VO proposed in~\cite{mur2015orb} is the representative traditional VO method. It is worth noting that the backend and loop closure are removed from~\cite{mur2015orb} for the sake of fairness.

The VO evaluation results are reported in Table \ref{tab:p_est}. The peformance of ORB-VO surffer from serious degradation cause by the textureless, reflective or dynamic objects. In comparision, our method achieves the best results compared to traditional monocular methods and other unsupervised methods. From the comparative illustration in Figure.~\ref{fig:pose}, we can see that scale drift are apparently suppressed compared to ORB-VO and Monodepth2. This is because the ego-motion in our method is constrained from two aspects: homography constraint from the road region and the photometric from all the scene. Combining these two constraints help resist the negative affect on ego-motion estimation from the disturb of dynamic regions.

Table \ref{tab:d_est} reports the comparative results between two groups of methods and ours. The first group is to recover the metric scale of estimated depth by using the per-image median ground truth scaling strategy denoted as "GT"~\cite{zhou2017unsupervised}. In this case, our method is trained without the prior knowledge of calibrated camera height. We can see that the accuracy of depth from our method are slightly better than that from Monodepth2~\cite{monodepth2} in most of the metrics. In second group, namely the last two rows in Table \ref{tab:d_est}, the estimated depth comes with metric scale from network. The DNet obtains the scale information by enforcing dense geometry constraints (DGC) \cite{xue2020toward}. Instead, our method recovers the scale during training process simply by using the ratio of the calibrated and estimated camera height. We can see that our method achieves comparable accuracy to DNet in a more concise way.

\begin{figure*}
\begin{center}

    \includegraphics[width=1.0\linewidth]{homography.pdf}
\end{center}
   \caption{Examples of homography matrix.We drew source points (green) and  transformed target points (red), and connected them with a line (blue) on the picture. The length of the line indicates the estimation error. Colored rectangle depict areas for comparision}
\label{fig:homography}
\end{figure*}

\begin{figure*}
\begin{center}

    \includegraphics[width=1.0\linewidth]{homographyv5.pdf}
\end{center}
   \caption{Visualization of homography photometric errors. We visualize the photometric error between the reconstructed image and the source image. The upper part of the picture is the reconstructed image, and the lower part is the visualized photometric error. From black to red indicates error from small to large. Colored rectangles depict areas for comparision.}
\label{fig:homography2}
\end{figure*}

\subsection{Homography Evaluation}

Since existing deep homogrpahy estimation methods are not aiming at a specific plane, they may fail when directly applied for road homography estimation because the road it not often dominant in the scene. Therefore we compare our methods with the traditional feature based methods using the reprojection error metric, which is depicted in
Figure.~\ref{fig:homography_score}. We can see that our method outperforms representative feature-based methods ORB and SURF, achieving the lowest reprojection error.

The visualized reprojection errors are compared in Figure.~\ref{fig:homography}. Observing from the enlarged local regions, we can see that the reprojected points almost completely overlap with the target points by using our method, while there are apparent offsets by using traditional methods. The reason might be that the extracted keypoints in feature-based methods distribute unevenly on the textureless road regions, which has a seriously negative impact on homography estimation. Instead, our method requires the estimated ego-motion and ground normal to meet densely road-aware homography constraint which leverages more effective information. The photometric error is also demonstrated in Figure.~\ref{fig:homography2}. It can be observed that the photometric errors near the road boundary area of our method are much smaller than feature-based methods, which further demonstrates the effectiveness of our road-aware homography estimation.

\begin{figure*}
\begin{center}

    \includegraphics[width=1.0\linewidth]{normal.pdf}
\end{center}
   \caption{Illustration of estimated ground normal. The red arrow represents the predicted normal while the blue arrow represents the ground truth.
   For visual convenience, we shift the start point of predicted normals by 2 pixels to the right to avoid overlaps with ground truth labels.}
\label{fig:normal}
\end{figure*}

\begin{figure}
\begin{center}
    \includegraphics[width=1.0\linewidth]{homography_score.pdf}
\end{center}
   \caption{Keypoint reprojection errors of the homography estimation produced by exisiting methods and our method.}
\label{fig:homography_score}
\end{figure}

\begin{table}
    \begin{center}
        \begin{tabular}{|l|c|}
        \hline
        Method & Error/deg \\
        \hline\hline
        GroundNet\cite{man2019groundnet} (Supervised) & 0.70\\
        \hline
        HMM\cite{dragon2014ground} (Unsupervised) & 4.10 \\
        Lu Xiong et al.\cite{xiong2020joint} (Unsupervised) & 3.23 \\
        Ours (Unsupervised) & 1.12 \\
        \hline
        \end{tabular}
    \end{center}
    \caption{Evaluation result of ground plane estimation on KITTI dataset. The ground truth normal vector is calculated based on the ground truth external parameters}
    \label{tab:ground_est}
\end{table}

\subsection{Ground Plane Normal Evaluation}
In this experiment, we verify the proposed method on test dataset used in GroundNet\cite{man2019groundnet}. We quantitatively compare our method with existing methods in Table \ref{tab:ground_est}. The angle between predicted and ground-truth normal is used as the evaluation metric. From Table.~\ref{tab:ground_est} we can see that the mean error of our method is 1.12 degree which are significantly smaller than other unsupervised methods~\cite{dragon2014ground} \cite{xiong2020joint}. Note that the performance of our self-supervised method is comparative to the supervised method GroundNet\cite{man2019groundnet}, which guarantee the accuracy. Though without groundtruth for training, the depth and homography estimation provide supervisory signal for Ground-CNN. The visualized results are shown in Figure \ref{fig:normal}, from which we can see that the predicted ground normal vectors are nearly identical to the ground truth even in the areas with significant varying or shadows (see the results in last row), which indicates the effectiveness and robustness of the proposed Ground-CNN.

\section{Conclusion}
In this paper, we propose a method that combines SFM and road homography estimation into a unified framework. Similar to \cite{zhou2017unsupervised}, the SFM part consists of a Depth-CNN and a Pose-CNN. Meanwhile, the Pose-CNN combine with a newly introduced Ground-CNN followed by a novel homography layer are used to solve the road homography. By designing a photometric loss, a dense homography loss and a depth smoothness loss, the whole network is trained end to end without groundtruth except for road segmentation provided by an off-the-shelf semantic segementation model (to limit the homography loss to the road pixels). In addition, the metric scale of depth and ego-motion can be recovered as long as the mounting height of camera is roughly calibrated. Extensive experiments are carried out on the KITTI benchmark to show that the proposed method significantly improves the accuracy of ego-motion and homography estimation. As future work, road or ground segmentation can also be jointly inferred by the network, making our approach fully unsupervised.

{\small
\bibliographystyle{ieee_fullname}

redpajama_set_name: RedPajamaArXiv


text:
Nathanja (Natanja) ist ein Vorname, abgeleitet aus dem Hebräischen.

Bedeutung
Der Name Nathanja letzt sich aus den Elementen נתן "er hat gegeben" und יהו jahu (Kurzform von JHWH): "der  hat gegeben".

In der Vulgata wird der Männername Netanja als Nathania, bzw. Natania geschrieben. Heute ist der Name überwiegend als Frauenname geläufig.

Namensvarianten sind die männlichen Namen Netanja und Jonathan.

Die Namen Nathan und Nathanael sind mit Nathanja verwandt.

Namenstag
Es wurde bis jetzt (Stand 2008) noch kein Kalendertag als Namenstag festgelegt

Bekannte Namensträgerinnen
 Nathanja Hüttenmeister (* 1967), deutsche Judaistin

Siehe auch
 Netanja

Weiblicher Vorname


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 Matthew Dear or Audion, techno music artist
 Audion receiver, a type of radio receiver that was originally designed to use the Audion signal detector


TheStreet.com and other media sources covered the successful completion of Macellum Advisors' activist campaign at Citi Trends in connection with the company's 2017 annual meeting of stockholders. Based on preliminary tabulations, Macellum nominee Jonathan Duskin was elected to the Board of Directors of Citi Trends at the annual meeting. The Olshan team representing Macellum included Steve Wolosky, Elizabeth R. Gonzalez-Sussman and Ron S. Berenblat.


text:
Q: bash string equality In bash, what's the difference, if any, between the equal and double equal test operators?
[[ "a" = "a" ]] && echo equal || echo not-equal
[[ "a" == "a" ]] && echo equal || echo not-equal
[[ "a" = "b" ]] && echo equal || echo not-equal
[[ "a" == "b" ]] && echo equal || echo not-equal

results in:
equal
equal
not-equal
not-equal

A: There's no difference, == is a synonym for = (for the C/C++ people, I assume). See here, for example.
You could double-check just to be really sure or just for your interest by looking at the bash source code, should be somewhere in the parsing code there, but I couldn't find it straightaway.

redpajama_set_name: RedPajamaStackExchange


At H2, our greatest focus is on improving the performance of our clients, both in their organizations as well as in their application of technology. With years of expertise in consulting services; implementing various forms of technology; and maintaining networks and systems, we provide our clients with a blended set of highly-advanced solutions and specialized services that are specifically targeted at improving results. We transform challenges into success that is concrete, maintainable, and scalable.
Our team of professionals have an excellent reputation as experts in planning and managing IT projects, programs, and portfolios, with considerable experience in providing a wide range of cyber and technology solutions as well as organizational performance analysis and large scale IT acquisition consulting. We form a strong partnership with our clients to identify opportunities that will bring the highest value to them and address their most critical challenges. We work tirelessly with their teams to transform their organizations.
We offer our clients our expertise in mitigating the risks, implementing systems that safeguard their data and protect the technology that keeps their businesses running.
The technology services team is highly specialized, and our company has become a recognized leader in the technology services industry.
The technology services team is highly specialized, and our company has become a recognized leader in the industry of technology services.
We have a team of professionally trained, certified, and highly experienced consultants ready to assist our clients in all aspects of Program and Acquisition Management.
At H2, we've had the opportunity and pleasure to work with many great organizations.


2013 Food Photographer of the Year competition, sponsored by Pink Lady.
The final judging is taking place at the moment and the winners of each category and an overall winner are to be announced at the awards ceremony in London on 23rd April.
Finalists are not permitted to disclose the images that have been selected for final judging until after the winners have been announced. The images shown on the attached screenshot from the competition website are a selection of the winners from 2012.
Sweeping plains dotted with palm trees, majestic sand dunes standing next to clear blue ocean waters, laid-back friendly people… and the largest meat-grills (parillas) I have ever seen! Just a few of my wonderful memories from a recent commission in Uruguay.
Full of vitamin C to fight off winter colds, and bursting with tangy citrus flavour, oranges are Torvehallerne's featured ingredient of the month for February. Visit their website to see 3 delicious recipes created by chef Marcus Sandemann, including my favourite – duck breast with fried apples, kale and orange sauce…mmmm! Photographs by Sarah Coghill.


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Would you be interested in and support a monthly DMR net?
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