text:
Computational Intelligence and Neuroscience
Computational Intelligence and Neuroscience / 2017 / Article
AbstractIntroductionRelated WorkConclusionConflicts of InterestAcknowledgmentsReferencesCopyright
Volume 2017 |Article ID 8710492 | https://doi.org/10.1155/2017/8710492
Shuqiu Tan, Dongyi Chen, Chenggang Guo, Zhiqi Huang, "Extra Facial Landmark Localization via Global Shape Reconstruction", Computational Intelligence and Neuroscience, vol. 2017, Article ID 8710492, 13 pages, 2017. https://doi.org/10.1155/2017/8710492
Extra Facial Landmark Localization via Global Shape Reconstruction
Shuqiu Tan ,1 Dongyi Chen ,1 Chenggang Guo ,1 and Zhiqi Huang1
1School of Automation Engineering, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu 611731, China
Academic Editor: Elio Masciari
Received04 Jan 2017
Revised26 Mar 2017
Accepted04 Apr 2017
Published23 Apr 2017
Localizing facial landmarks is a popular topic in the field of face analysis. However, problems arose in practical applications such as handling pose variations and partial occlusions while maintaining moderate training model size and computational efficiency still challenges current solutions. In this paper, we present a global shape reconstruction method for locating extra facial landmarks comparing to facial landmarks used in the training phase. In the proposed method, the reduced configuration of facial landmarks is first decomposed into corresponding sparse coefficients. Then explicit face shape correlations are exploited to regress between sparse coefficients of different facial landmark configurations. Finally extra facial landmarks are reconstructed by combining the pretrained shape dictionary and the approximation of sparse coefficients. By applying the proposed method, both the training time and the model size of a class of methods which stack local evidences as an appearance descriptor can be scaled down with only a minor compromise in detection accuracy. Extensive experiments prove that the proposed method is feasible and is able to reconstruct extra facial landmarks even under very asymmetrical face poses.
Facial landmark localization is the first and a crucial step for many face analysis tasks such as face recognition [1], cartoon facial animation [2, 3], and facial expression understanding [4, 5]. Most facial landmarks are located along the dominant contours around facial features like eyebrows, nose, and mouth. Therefore facial landmarks on a face image jointly describe a face shape which lies in the shape space [6].
For the last ten years remarkable progress has been made in the field of facial landmark localization [7, 8]. Among a large number of proposed methods, the most popular solution is to treat the facial landmark localization problem as a holistic shape regression process and to learn a general regression model from labeled training images [9, 10]. Following this shape regression idea, various methods try to model a regression function that directly maps the appearance of images to landmark coordinates without the need of computing a parametric model. All facial landmarks in a shape are iterated collectively and the relationship between facial landmarks is flexibly embedded into the iteration process. On the other hand, to generate enough description of face images, multiscale local feature descriptors are typically adopted in most shape regression methods. For example, cascaded pose regression (CPR) [7] was first proposed to estimate general object poses with pose-indexed features and then extended for the problem of face alignment in explicit shape regression (ESR) [11] method. ESR combines two-level boosting regression, shape-indexed features, and correlation-based feature selection. As another example, supervised descent method (SDM) [12] and its extensions also have shown an impressive performance in the field of facial landmark localization. These kinds of methods stack shape-indexed high dimension feature descriptors and train regression functions from a supervised gradient descent view.
However, facial landmark localization still meets great challenges in practical applications, such as handling pose variations and partial occlusion while maintaining moderate training model size and computational efficiency. In SDM and its improved methods, the dimension of regression matrix in each stage keeps the same with the stacked feature descriptors, where the magnification of dimension is relevant to the number of feature points. This substantially limits the use of feature descriptors with high dimension. In this type of methods, solving such high dimensional regression matrices occupies a large memory and the computation of both training and testing is not very efficient.
In this paper, we consider the possibility of only training a subset of available facial landmarks while in predicting stage the "missing" landmarks are restored by the inner shape correlation as if they were trained before. In this way, both the training time and the model size can be scaled down by only compromising a minor detection accuracy. Following this idea we propose a global shape reconstruction (GSR) method for predicting extra facial landmarks with limited models; see Figure 1. The concept of the proposed method is similar to the linear interpolation between facial landmarks. But there still exists a major difference since the shape prior information is adopted, which allows the proposed method to restore facial landmarks under asymmetric poses. Before the training stage, a set of shapes are collected and aligned based on the face bounding box. Then a sparse shape dictionary is trained to obtain more compact exemplars with inner shape correlation. Regressors such as SDM are trained on datasets with reduced facial landmarks. Global shape constraints are introduced on the final output of cascade regression. From another perspective, previous works that are designed or trained for fixed number of facial landmarks can interpolate more landmarks by applying proposed shape constraints.
The flowchart of the proposed GSR method.
The main contributions of this paper are the following: we exploit sparse shape constraints for nonlinear restoring extra facial landmarks comparing to landmarks used for training. Specifically, we propose two strategies, named constrained global shape reconstruction with Procrustes analysis (C-GSR-PA) and simple global shape reconstruction with Procrustes analysis (S-GSR-PA), respectively, to utilize the facial landmarks correlation in landmark reconstruction procedure. We study the performance between model compression and alignment error in extensive experiments. As mentioned above, using the proposed method existing works can train models on less landmarks while predicting equivalent results, but this may introduce corresponding alignment error during reconstruction. The experimental comparison results and conclusions are given in the end.
2. Related Work
Facial landmark localization methods can be roughly divided into two categories [7]: generative methods versus discriminative methods. Generative methods build generative models for both the face shape and appearance. They formulate face alignment as an optimization problem and generate an appearance model instance that is fit for the test face image. Discriminative methods typically independently learn regressors for each facial point and introduce a global shape model for regularization.
The active shape model [13] and active appearance model (AAM) [14] are the most well-known family of generative methods with much follow-on works. They are statistical models that attempt to describe facial appearance variations in terms of an underlying parameter space. Recently some extensions have been proposed. Matthews and Baker proposed a project-out inverse compositional algorithm (POIC) [15] to decouple shape from appearance and showed an extreme fast convergence speed. Different from POIC that projects out the appearance variations, the simultaneous inverse compositional (SIC) [16] algorithm has shown to be more robust than POIC for generic AAM fitting. Besides SIC, the alternating inverse compositional (AIC) [17] algorithm solves two separate minimization problems, one for the shape and one for the appearance.
In contrast to generative methods, discriminative methods such as deep network based methods and cascade regression based methods have attracted much attentions in recent years. In the deep network domain, Sun et al. [18] first handle the alignment task by a three-level carefully designed convolutional network. Then deep convolutional neural network (CNN) is introduced by Zhang et al. [19]. Zhou et al. [20] design a four-level convolution network cascade in a coarse-to-fine manner. Lai et al. [21] propose an end-to-end CNN architecture to learn discriminative shape-indexed features. Cascade regression is introduced into face alignment by Cao et al. [11] in their work. They design a two-level framework by again investigating boosting regression as the stage regressor. Robust cascade pose regression (RCPR) [22] is proposed to include occlusion information during learning and to pool robust features by indexing pixel features between facial landmarks. SDM [12] proposed by Xiong and De La Torre presents a cascaded linear regression formulation derived from a statistical approximation of Newton optimization. Then SDM is extended into a global optimization method called global SDM [23] to avoid a possibly local minimum. Random subspace SDM [24] is another extension and is proposed to handle the underdetermined issue and the overfitting problem in SDM.
As discussed in ESR [11] and dual sparse constrained cascade regression (DSC-CR) [25], local evidence is only sufficiently strong for a few prominent facial landmarks, such as the corner of face parts. But most of the others are not sufficiently conspicuous and cannot be reliably characterized by their image appearance. Therefore shape constraints should be explicitly introduced. Unlike the DSC-CR using a heuristic manner, we directly incorporate the sparse shape constraints into a linear regression function. In the current literatures, almost all the methods aim to design a robust feature mapping architecture or a specific form of stage regressor. In this paper, we explore a way to train models on a reduced landmark configuration and then reconstruct desired extra facial landmarks in the testing stage.
3. Global Shape Reconstruction Method
In this section, we present the proposed method for extra facial landmark localization in detail. First we give a brief review of the popular SDM framework. Then the training process on reduced facial landmarks is described. Finally, extra facial landmarks are predicted via proposed sparse shape constraints. An approximate sparse shape reconstruction method is also presented for reconstructing just a small number of extra facial landmarks.
3.1. SDM
The shape of a face image is here defined by a vector of facial landmarks coordinates in shape space; that is, , where is the number of landmarks and is the coordinates of the th landmark. Given an image and an initial shape , SDM progressively refines the face shape by estimating a shape increment , which is added up to the shape estimate of previous stage. This can be formulated aswhere is the stage regressor. In the case of SDM, is generalized into a linear regressor . is a nonlinear feature mapping function that stacks shape-indexed feature descriptors into a single vector and is the total number of regression stages. Since the feature mapping function is related to the previous shape estimate, the output of the function is also referred to shape-indexed features. In the training stage, the stage regressors are learned sequentially.
3.2. Training on Reduced Facial Landmarks
Previous works mostly focus on designing a robust feature mapping function or a specific form of stage regressors [7]. Practically, we found the SDM method has a great demanding memory due to the operation of stacking feature descriptors. This substantially limits the use of high dimensional discriminative feature descriptors. In this type of methods, solving such high dimensional regression matrices occupies a large memory and the computation of both training and testing is not very efficient. Therefore we propose a method to train models on reduced facial landmarks and then localize extra facial landmarks in the testing stage. Another benefit that comes with the proposed method is that it is able to generate more constrained outputs with a given model. Note that a specific form of stage regressor for model training is not the emphasis, and here we adopt the SDM method to serve as a training framework.
Given a set of labeled face images , along with their ground truth locations of facial landmarks , where is in the shape space, facial landmarks are selected out of the original landmarks, which means and makes in the shape space. Let extract shape-indexed features on the newly formed shape . The SDM method seeks an optimal at each stage, which minimizes the following fitting cost:where is the shape estimate of image at stage. Then the shape estimate of the next stage is updated by . Equation (2) is very similar to the minimization function in RSSDM, but the regression target is different. In RSSDM, the subspaces are formed by random selecting features in the whole feature space while regressing the whole shape. However in this paper the optimization function is regressed in the shape subspace.
3.3. Extra Facial Landmark Reconstruction
Motivated by sparse shape constraint proposed in DSC-CR [25], we adopt the sparse signal representation to reconstruct extra facial landmarks; that is, . Although the restoring problem is ill-posed, the sparse shape representation demonstrates robustness in regularizing this problem. To be more precise, let denote an overcomplete shape dictionary containing exemplar shapes . That is, any face shape can be reconstructed as , where is a coefficient vector with a few nonzero entries. Since the dictionary is overcomplete, the above equation is underdetermined and has a unique solution if is sparsest. As for the shape of reduced facial landmarks , a similar sparse decompose equation can be formulated as . The coefficient vector of sparse decomposition is reused in extra landmarks restoration. To summarize, for every input shape a corresponding sparse coefficient vector is solved by using the dictionary . The shape dictionary will be combined to the coefficient vector to generate the desired output . In the following we propose two strategies to train the dual dictionaries and .
3.3.1. Constrained Global Shape Reconstruction (C-GSR)
We call this a constrained strategy since the sparse coefficient vector is reused in a regressive manner. A number of face shapes is collected for training the dictionary . The dictionary can be obtained by minimizing the following equation:In practice, we use the -singular value decomposition (-SVD) [26] and orthogonal matching pursuit (OMP) [27] to solve the -norm problem in (3). As long as the desired coefficients are sufficiently sparse, signals can also be recovered by instead minimizing the -norm form. Obviously, the dictionary can be acquired the same as (3). However in practice, we find that a simpler way to get a dictionary is to pool and normalize corresponding dimensions of . More specifically, let denote a set of row vectors , ; we can construct the dictionary by pooling a subset rows of using indexes of the landmarks. This is quite straightforward because each atom in the dictionary actually represents a face shape, and the pooling operation just extracts a subshape for the same face. Then the atoms in dictionary should be normalized to unit length. The coefficients are calculated fromwhere and are sparsity degrees, respectively. Again we utilize the OMP to solve (4). The goal is to make and as close as possible; thus a linear regression error is minimized by the following equation:where denotes the linear regression matrix to be optimized. We apply the support vector regression (SVR) realized in LIBLINEAR toolbox [28] to solve (5). In the testing stage, extra facial landmarks can be reconstructed from , as illustrated in Figure 2. To reduce the scale and translation drift in the process of C-GSR, we finally apply a Procrustes analysis between the newly reconstructed landmarks and the original selected landmarks. This is also denoted as C-GSR-PA.
The proposed C-GSR method.
3.3.2. Simple Global Shape Reconstruction (S-GSR)
To further simplify the C-GSR method, an approximation is made as follows: after calculating all the sparse coefficient vectors in C-GSR, the sparse coefficients are considered as the rough approximation of the coefficients . Then extra facial landmarks can be calculated from , when , as illustrated in Figure 3. Comparing to the C-GSR strategy, S-GSR does not need to train a regression matrix in advance and requires a less computation resource. Combining with a facial occlusion detection method, S-GSR may correct a small number of occluded points based on the points of high prediction confidence.
The proposed S-GSR method.
4. Experiments
4.1. Datasets
Experiments are conducted on two datasets, namely, LFPW-68 and HELEN-68.
LFPW-68. The labeled face parts in the wild (LFPW) dataset [29] include 1,400 face images (1,100 images collected as the training set and the other 300 images collected as the testing set). 29 points are marked for each image. This dataset is one of the most popular datasets to benchmark facial feature detection methods in uncontrolled conditions during recent years. But in this paper, we use another version of 68 points annotations to evaluate the following experiments. Images and annotations are downloaded from the website provided by Intelligent Behavior Understanding Group [30]. And this dataset has 800 training set images and 224 testing set images.
HELEN-68. The HELEN dataset [31] contains 2,300 high resolutions in the wild face images and 194 points are marked for each image. All collected face images have arbitrary expressions, poses, and illumination. In this paper, we again use a version of 68 landmark annotations [30] to test the following experiments.
4.2. Implementation Details
As an overall setting, every training image is cropped by detecting a face bounding box and then resized to pixels and flipped together with the landmark coordinates to enlarge the training data size. To achieve a better generalization ability, 10 initial shapes are randomly sampled for each training and testing image. The cost in the SVR is set to 0.005. For the SDM method, 5 stages are used in the cascade regression. Histogram of gradient [32] is adopted as the feature descriptor with a dimension of 124. For the RCPR method, we use the default parameters reported in the original paper: 100 iterations, 15 random fern regressors, 5 restarts, and 400 features. Experiments are all running on a Laptop with an Intel Core i5-5200U CPU, a 12 GB installed memory, and a Matlab R2014a coding environment.
4.3. Parameters Evaluation
In this section, we evaluated the reconstruction error of (3) with respect to two most important parameters, the shape dictionary size and shape sparsity, respectively, on the LFPW-68 points testing set. For the sake of simplicity, training samples can be directly normalized into atoms in the dictionary. But here -SVD is utilized to train a compact shape dictionary. A grid search for two parameters is performed. The size of shape dictionary is varied from 200 to 800 while keeping the shape sparsity constant. Then the shape sparsity is varied from 5 to 35 while fixing the shape dictionary size. The comparing results are plotted in Figure 4. It shows that the normalized alignment error of reconstructed shapes first goes down with the growth of shape dictionary size. Then the error curves have an upward trend when shape dictionary size is larger than 500. This shows that, under a given sparsity, the size of the shape dictionary trained by -SVD has an optimal value and is not the larger the better. Figure 4(b) gives the normalized alignment error of each shape sparsity when shape dictionary size is set to 500. It shows that the alignment error monotone decreases with the shape sparsity increasing because of the greedy nature of OMP algorithm. The larger the sparsity, the smaller the reconstruction error. But the reconstruction error begins to decrease slowly after the sparsity degree exceeds 20. Considering both performance and solving speed, the turning point at sparsity 20 is chosen for both the shape sparsity degrees and .
Parameters evaluation on LFPW-68 testing set.
4.4. Reconstruction Strategies Evaluation
In this section, we study the reconstruction performance under different extra facial landmarks reconstruction strategies. Two strategies of C-GSR and S-GSR with the Procrustes analysis are denoted with a "-PA" postfix. Experiments are all carried out on LFPW-68 points testing dataset; that is, . Here experiments are conducted on ground truth shapes since we only intend to find out the best model simplification strategy and not to test generalization ability. It will be tested in latter sections.
In Figure 5, we plot the normalized reconstruction error with respect to the number of reduced landmarks, that is, the size of . The size of is varied from 22 to 68. We reconstruct extra facial landmarks by using proposed strategies. It shows in Figure 5 that the reconstruction process has an inherent alignment error 0.0185 when , which means no extra landmarks are actually reconstructed. In this case, the error is introduced in the process of coefficient solving and shape synthesis. With the size of growing, all the reconstruction error curves have a decrease trend. The error curve of S-GSR is obviously steeper than the error curve of C-GSR, indicating that the size of has a great influence on the S-GSR method. Comparing S-GSR with S-GSR-PA, it can be found that the Procrustes analysis makes a difference when is small. But it gradually plays a less role in rectifying reconstruction shifts when grows larger. From the enlarged view in Figure 5 it shows that when is smaller than 62 points, the C-GSR-PA achieves a far stable performance than S-GSR-PA. This is due to the rough approximation from sparse coefficients to in S-GSR-PA. But the S-GSR-PA shows a comparable performance when exceeds 62 points.
Reconstruction strategies evaluation on LFPW-68 points testing dataset.
In order to get an intuitive understanding of the proposed method, we give a visualization of five different landmark configurations in Figure 6. The first row in Figure 6 illustrates the configuration pattern of reduced landmarks, and the rest two rows give the reconstruction results of C-GSR-PA and S-GSR-PA, respectively. In columns (a), (b), and (c) it is shown that more facial landmarks contribute to more accurate reconstruction performance. The S-GSR-PA has a more significant reconstruction error than the C-GSR-PA when is relatively small. But if is large enough, a few extra facial landmarks can be restored accurately by S-GSR-PA. To clarify the robustness of proposed method, we also illustrate the reconstruction results when half of the face landmarks are removed. This task is challenging and practical because large pose variations often exist in the wild images. It shows in columns (d) and (f) that the proposed strategies can effectively explore inner shape constraints and reconstruct the other half face landmarks even under a very asymmetry case, which is impossible for a typical linear interpolation algorithm.
Visualization of different landmark configurations on LFPW-68 points testing dataset.
4.5. Evaluation of C-GSR-PA on Two Facial Datasets
In this section, we evaluate the performance of the proposed method in four aspects, namely, the normalized alignment error, training time cost, testing time cost, and training model size, on two facial datasets. We first train models as described in Section 3.2. Then extra landmarks are reconstructed by proposed GSR method. SDM is chosen to serve as a cascade regression framework. In order to give an error comparison we use datasets where the number of labeled landmarks is more than 50. Therefore the alignment error can be calculated between reconstructed landmarks and labeled landmarks.
In Figure 7, we plot the cumulative error distribution (CED) curves of different reconstruction configurations. It shows in Figure 7 that using a reduced landmark configuration has a slightly less prediction accuracy than using the original SDM method. But the performance is about the same when five configurations are tested on LFPW-68 dataset. However, the performance loss in reducing landmarks at the training stage is still acceptable when considering the training time compression and model simplification. The comparing results are illustrated in Figure 8.
Cumulative error distribution (CED) curves of five reconstruction configurations on (a) HELEN-68 and (b) LFPW-68 datasets.
Normalized alignment error, training time cost, testing time cost, and training model size of five reconstruction configurations on two facial datasets: (a) HELEN-68 and (b) LFPW-68 datasets.
From Figure 8 it shows that using more landmarks for model training contributes to lower testing errors. But the difference is not significant comparing to the other three performance indicators. As is shown in Figure 8, the proposed method which trains on 22 facial landmarks and then reconstructed into 68 landmarks only has a 0.48% (LFPW-68) and 0.96% (HELEN-68) accuracy loss, comparing to the original SDM method which trains complete 68 landmarks. However, taking the experimental results of LFPW-68 dataset as an example, the method proposed in this paper has made significant progress in the following aspects compared with the original SDM method: 6.4 times faster in model training, 1.2 times faster in dataset testing, and 8.6 times smaller in model size.
For a better understanding, we also present the detection results with predicted landmarks labeled as green dots in Figure 9. It can be found in Figure 9 that the number of training landmarks has a positive effect on frontal images especially when the face deflection is severe. The proposed method fits well with the base points of the regression output and also gives a reconstructed shape that conforms to the contour of the face. In addition, it also shows in the figure that the landmarks located at the turning points of contours can promote the reconstruction precision. In general, by using only a 22-landmark configuration we manage to restore a 68-landmark configuration with a comparable alignment accuracy.
Detection results on LFPW-68 and HELEN-68 datasets. The first column gives the reduced landmark configuration for model training. For the rest of the columns, red dots on the images are the landmarks predicted by SDM and green dots on the images are the landmarks reconstructed by C-GSR-PR method.
4.6. Evaluation of S-GSR-PA on Reconstructing a Small Number of Facial Landmarks
As discussed in Sections 3.3.2 and 4.4, S-GSR-PA has a comparable performance on reconstructing a small number of facial landmarks. Therefore we design the following experiments and test on the LFPW-68 testing dataset. A pixels' occlusion region restricted in the shape bounding box is randomly generated for each testing image. This size is selected for that only a few facial landmarks need to be occluded by the generated region. Then both the SDM and RCPR methods are tested on this artificial occlusion testing dataset for five times. Finally we run the above two methods to locate a complete facial landmark and then apply the S-GSR-PA method for refining the locations of occluded facial landmarks. Under this setting the algorithm of face occlusion detection is not discussed in this paper and the occluded regions are presumed to be known. Experimental results are plotted as CED curves in Figure 10. It shows in Figure 10 that the operation of facial landmark reconstruction helps improve the prediction accuracy of the SDM method. And it also shows a limited improvement in adjusting the RCPR method. This might be that the RCPR method can explicitly detect occlusion and use robust shape-indexed features. In general, Figure 10 clearly demonstrates that the S-GSR-PA method has a positive effect on rectifying occluded facial landmarks.
CED curves of four methods on artificial occlusion testing dataset.
In this paper, we present a global shape reconstruction method for locating extra facial landmarks comparing to facial landmarks used in the training phase. By applying the proposed method, both the training time and the model size of a class of methods can be scaled down with only a minor compromise in detection accuracy. Specifically, we propose a constrained strategy (C-GSR-PA) which exploits the sparse coefficients constraints in face shape correlations. Extensive experiments show that it is able to reconstruct up to three times facial landmarks even under very asymmetrical face poses. We also propose a simplified strategy (S-GSR-PA) which shows comparable performance when reconstructing a few facial landmarks. It does not need to train a regression matrix in advance and require a less computation resource. It has potential in refining a small number of unreliable predictions.
The authors declare that there are no conflicts of interest regarding the publication of this paper.
This work is supported by National Key Research & Development Plan of China (no. 2016YFB1001401) and National Natural Science Foundation of China (no. 61572110).
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Copyright © 2017 Shuqiu Tan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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POF got its start in as Plenty of Fish and is now one of the world's largest free dating services with more than , members. If you are new to POF, you are not alone, about 70, new users up every day. POF also usually has fromduring a weekday afternoon to 1.
With these types of s, members are guaranteed to meet a variety of singles on the service actively looking for friendship, casual dating, and serious relationships. It starts out with basic profile information about you and what you are looking for. Initial up questions cover children, marital status, interests, smoking and drinking habits, religion, occupation, income, family situation, relationship history, and more. Users then personalize their profiles with a headline, an essay description, and a list of interests.
An optional essay on conversation starters is also available. Most members will be interested in searching and POF allows you to do that easily on their app and website once you have finished setting up your profile. Just tap on the search button and your are brought up right away using your default Dating Preferences that you entered when you created your profile.
You can further refine your search filters easily enough by modifying the location you want to view and by the different sections of the profile including Bio, Background, and Lifestyle attributes. Almost all of the profile attributes can be used as filters, which is a lot and means you can really refine your search. Once you start looking through your search you can Like the profiles that you find interesting and message them as well.
Another fun way to find local members is to use "Meet Me". This is a matching type game that not only uses Plenty of fish dating website reviews Dating Preferences but other important criteria to show you potentially ideal matches one at a time. If you both end up liking each other that is considered a Mutual Match. You will both be notified of such a match and can then start to message each other. Members who use one of the POF apps get a unique feature called Live. This is where members can live stream video of themselves and other members can watch and interact with them by chatting and sending them hearts and virtual gifts.
You can find live streamers by popularity, those who are near by, and other common filters. This is a type of virtual speed dating where you get 90 seconds to ask prompted questions of your date. If you both like what you see and hear you will be matched and allow to continue to do private video chatting.
If things are not working out, you can tap the Next button to move on to the next date in the queue. A free membership allows for full access to the site and apps, Plenty of fish dating website reviews Searching, Likes, Live Streaming including NextDateand communication with other members, but paying has its perks.
Members who upgrade will appear higher in searchhave access to users who have Liked them in Meet Me, the ability to see if sent messages were read, the ability to see who viewed your profile, and online ad removal. POF also allows free and upgraded members to buy Tokens. Tokens can be used to Boost your profile to the top of all lists Search, Meet Me, etc They have succeeded in becoming a dating service for all singles by not only offering many search tools but constantly innovating and adding new features as well. We give Plenty of Fish, a 4.
Note: See this for a full list of past awards.
About vipkino.fun reviews
POF is one of the few dating services who do not ask if you want to connect your to a social networking service like Facebook. They also ask for all of your profile information up front during up most is mandatory. A lot of services tend to only ask the basic profile information and then allow the user to start using the service meaning a lot of the profiles on these services lack substance. When you register for your POF useryou will be asked for the following information:.
For those profile attributes which are important to customers interested in free dating services like POF we have included the select-able options to show the type of members you will be able to find on this dating service and what is easily searchable. POF tends to attract those singles who are 30 years and older, who have a decent job or are retired, and who may be a single parent.
Your profile and photos will be reviewed by a moderator before being displayed on the site. You can change your birth date and gender within two weeks of ing up; after two weeks it is assumed to be correct and can't be changed. This prevents people from trying to trick the matching system to give them different since members can control the age range of those who can contact them. When you edit your Plenty of fish dating website reviews, you can also hide your profile from others preventing it from showing up anywhere on the site or app.
You can also adjust your Mail Settings at this point.
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Other mail settings relate to the type of members who are allowed to send you messages through the POF service. See the Communication section below for more on what these settings are. Under the Mail Settings you also can disable your own profile views from being tracked along with a list of the users you have blocked you can also unblock users from this. To protect users s from unauthorized access and to help prevent scammers from ing the POF dating service all members must verify their by providing their mobile phone after logging into the service.
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POf will send the member a text with a secret code that they can then enter on the verification. This verification process for the is only required to be done once per device as long as the device supports cookies which accesses POF. For example, if you use your laptop to access POF. Members who don't have a mobile phone that can receive SMS text messages are required to contact POF customer service to verify their a different way. For more information please see this article about the POF verification process. POF offers a free membership which includes communication and a paid upgrade option.
Upgrading your membership triples the views of your profile and more than doubles your chances of meeting someone special.
POF also uses a virtual Plenty of fish dating website reviews called Tokens. Tokens can be purchased separately and then used for a of premium features. Finally, if you are using the Live! Any virtual gift you send in Live earns the member Diamonds which motivates them to continue broadcasting.
These Diamonds can be traded in via the App for cash rewards or Live credits. Plenty of Fish offers a vast of tools to view and communicate with other members. Almost all tools except Live! The layout is different between the app and the website, so most tools may not be found in the same location.
Most of these features can be found when viewing a user's profile directly or within the Meet Me, Search and Match. Plenty of Fish contains an in-depth search tool found both on the website and app. The service also has a decent automated matching system for those who are interested in meeting people based on compatibility.
POF use to have a much more detailed "Ultra Match" automated matching system and several different personality tests but those were removed in a past update to help streamline the service and to enable POF to concentrate on the most member used features.
POF is all about searching and probably has one of the most detailed search feature of any dating service we have come across includes the app and desktop. Clicking on the "Search" menu or Search icon on the app will return your default search based on your Dating Preferences.
On the app, the starting Search acts as the main POF Dashboard and includes not only a summary list of your search but also summaries of who is on Live, who has Viewed your profile, those members Nearby, your Matches, and the profiles you have Liked. Tapping on a profile will take you to the full profile view. In the app you can also view the full lists of all Plenty of fish dating website reviews by tapping the "View All" button.
The Search has a "Refine Search" button on the app which will take you to a new screen so you can update your search filters. On the website these filters are located on the same screen as the in the right column.
The search filters are organized by Location, Bio, Background, and Lifestyle. This corresponds to how a profile is organized and allows you to search on almost all parts of the profile displaying searches that can be as broad or as refined as you wish. The on the website are organized in a gallery type format while on the app they are listed one after the other. Each result shows the main profile photo, the Username, Age, Location, and what type of relationship the person wants.
The search tool is available to both free and upgraded members except for Username search which is only available after you upgrade. On the website, other Search s are accessible from the top menu bar including Plenty of fish dating website reviews that show Online members, New Members or First Look on the appRecommendations app onlyand My City or Nearby on the app. The app has the same Search s but they can be accessed either from the main Search Dashboard as mentioned above or from the Search itself.
Plenty of Fish has a couple of options for users who want a more automated matching approach to dating. Available only on the POF app, Live! Whether you are viewing a broadcast or are doing the streaming you are able to favorite people that spark your interest. As you build connections you can send virtual gifts and chat with members during their streams to further standout see tools above for more info.
NextDate is part of Live and is virtual speed dating. From the Date tab, tapping the heart icon at the bottom of the screen starts NextDate.
Every 90 seconds you will be connected with a Date through a 2-way live video stream. Each of you can ask prompted questions to your date. If you both tap Match by the end of the speed date, you will then be able to do a private 1-on-1 stream.
Your date will also be added to the "My Dates" section. If things are not going well, you can end your speed date early by just tapping on the Next button. Within NextDate you also now can go on Blind Dates. The singles who wish to do a Blind Date are found in the "My Dates" section and are highlighted in blue. Blind Dates work similar to the regular NextDate dates except the participants video stars off blurred and slowly over the date becomes less blurred.
When the time runs out the video is completely clear revealing who you were on a date with. POF was originally called "Plenty of Fish" and used the domain plentyoffish.
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Our vision is for a Wales that is simply a better place.
The Design Commission for Wales was established by the National Assembly for Wales to promote good design.
We support local planning authorities, developers and clients to capture the value of high quality design for better outcomes and a better return on investment.
We nurture design talent for a skilled workforce, necessary for growth and innovation.
By promoting good design and communicating its benefits, we add value and help to support well-being and enhanced quality of life for the people of Wales.
The Commission knows that the costs of bad design represent a risk to developers and investors; reduces value for the public purse; undermines environmental quality, climate resilience, public health and well-being.
Maximises efficiency and value for money.
Focuses on users, maximising ease of use, accessibility and inclusiveness.
Uses resources and energy efficiently, contributing to carbon reduction.
Has been shown to significantly improve patient recovery times in healthcare.
Has been shown to reduce the public health problems linked to poor housing.
Reduces maintenance, costly refurbishments and running costs.
Makes products, places and buildings more attractive.
Adds value and enhances public good.
Good design makes everything better.
The Commission promotes good design in four ways. Please contact us to find out how we can help you capture the value of good design.
The national Design Review Service provides opportunities for early consultation on plans and projects throughout Wales as well as access to expert input prior to the submission of planning applications.
Client support for commissioning clients provides help and guidance during the early stages of developing the brief and securing the right design team.
Events, publications and networks that raise awareness, stimulate wider debate and communicate the benefits of good design. Our HATCH network provides a platform for emerging design talent and fresh thinking shapers of the built environment.
The Design Commission for Wales promotes good design across sectors.
We value openness, transparency and mutual respect in a culture where knowledge is shared with all our stakeholders.
The Commission is an expert body. It is not a membership organisation or professional body. It does not represent the interests of any single profession.
To promote design practice that is compatible with the Welsh Assembly Government's Sustainable Development Scheme, promoting best practice in energy efficiency, waste disposal and public transport.
To give due regard to promoting excellence in day to day developments, like housing estates and industrial units, as well as promoting excellence in prestige projects.
Comisiwn Dylunio Cymru Design Commission for Wales is the trading name of DCFW LIMITED, Private Limited Company No: 04391072 incorporated in England and Wales as a wholly owned subsidiary of the Welsh Government. Its Registered Office is at 4th Floor, Cambrian Buildings, Mount Stuart Square, Cardiff CF10 5FL.
The Team and all but two of our Directors.
Mark Hallett and Ewan Jones were unable to join us for this snapshot, but you can scroll to find their details below.
Carole-Anne Davies is Chief Executive of the Design Commission for Wales. Born in Brynmawr, she was educated at Brynmawr Comprehensive School and the Open University. She is a humanities graduate and passionate advocate of the value of culture and the arts in a variety of settings. A career predominantly in senior management roles followed her time in industry with Thorn EMI and she held roles as Director of Cardiff Bay Arts Trust; Trustee at Amgueddfa Cymru National Museum Wales and consultant to the Scottish Government. In 2015 she was appointed founding Chair of The Gregynog Trust. Carole-Anne established a co-production business model at DCFW integrating the expertise of independent, multi-disciplinary, private sector professionals with that of the core staff team. She is an alumna of the CSCLeaders Commonwealth International Study Conference, of Harvard Kennedy School Executive Programme and the Cambridge Institute for Sustainability Leadership (CISL). She is a Fellow of the UWTSD, an Honorary Member of the Royal Town Planning Institute, Life Fellow of the Institute of Welsh Affairs. She is a very, very keen gardener.
Sue has an MBA and an MSc HRM and looks after HR, finance, Health & Safety, administration and team support. Sue is a member of CIPD and has 30 years' experience in managerial and supervisory roles, administration and finance, employee welfare, policy development, contractual and personnel management. After hours Sue enjoys creative crafts and family activities.
An urban designer and planner Jen has held the position of Design Advisor at the Design Commission for Wales since October 2014. She has more than seven years' professional experience working at south Wales-based private sector firms, following completion of her degree in City & Regional Planning and her Masters in Urban Design at Cardiff University. Jen is a fully accredited member of the Royal Town Planning Institute (MRTPI).
Jen's role at the Commission includes developing and promoting DCFW's design services, events and engagement programme throughout Wales. Jen is involved in DCFW's engagement with residential and regeneration projects in Wales as well preparing guidance and providing client support.
In her previous role at Cardiff-based planning and design consultancy The Urbanists, Jen led a diverse range of urban design, planning and regeneration projects for public, private and third sector clients. She has delivered design concepts, town centre strategies, environmental improvement schemes and planning applications as well as developing engagement and training programmes. Jen led the team appointed by Welsh Government to review the effectiveness of Design and Access Statements in Wales as part of the wider review of planning in Wales.
Wendy is a Design Advisor with the Design Commission for Wales, a member of its Design Review Panel and a professional consultant working in both private and public sectors.
Wendy studied at Cardiff University completing both a Bachelor in City & Regional Planning and a Masters in Urban Design. Her experience includes regeneration strategy and delivery with Newport Unlimited Urban Regeneration Company, planning and urban design with private sector design studio The Urbanists and time with the Planning Inspectorate of England & Wales where she was involved with the Nationally Significant Infrastructure Projects and Local Plans teams. Wendy has a particular interest in transport-led placemaking and regeneration.
Ian is Group Director of Development and Asset Management at Cynon Taf Community Housing Group and leads their asset management, maintenance, planned investment and development functions. Ian is a chartered town planner and qualified urban designer, receiving his Honours degree in City & Regional Planning and Masters in Urban Design from Cardiff University. He worked in the private sector and subsequently in Newport City Council's Major Applications team as Principal Urban Designer, before joining Newport City Homes and leading their ambitious regeneration programme for the Pillgwenlly area of Newport. Ian has long experience of, and is a passionate advocate for the Commission and its Design Review Service.
Elinor Gray-Williams is a Chartered Architect and RIBA Specialist Conservation Architect. She joined Donald Insall Associates in 2007 after completing the SPAB Lethaby and Plunket Scholarships. Elinor leads the Conwy office of the firm and is an experienced historic buildings architect with a strong commitment to Wales and its heritage. Elinor enjoys the challenges of designing new buildings and interventions within historic settings, and works creatively to maximise opportunities for sustainability.
Mark Hallett is Director of Igloo Regeneration and development manager of the Igloo Regeneration Partnership, described by the UN as the world's first sustainable property investor and the only substantial socially responsible real estate vehicle in the UK.
Phil is a partner and Divisional Director of the Built Environment division, Blake Morgan. He has considerable experience of large-scale public and private development work, joint ventures, regeneration projects and property transactions particularly relating to the governmental, health and education sectors.
Ewan Jones is a partner at Grimshaw extensively involved in their transport and civil engineering work, masterplanning and commercial projects.
Ewan led Grimshaw's successful bids to join frameworks with BAA and TfL, working on masterplans and strategic studies for both clients. He was project architect for the Stirling Prize shortlisted Amsterdam Bijlmer ArenA station and for works at Paddington station. Ewan designed the award winning Newport City footbridge and leads Grimshaw's bridge design work.
He works closely with major developers and leads the practice's London office building projects. Following completion of 25 Gresham Street, now Lloyds-TSB's head office, he gained planning consent for redevelopment of the former London Stock Exchange site and led design of The St. Botolph Building for Minerva. His team are now preparing proposals for a major commercial development alongside Paddington station.
Ewan's work includes architectural component design for London's Crossrail scheme and he is Director of Architecture for Sydney's North West Rail Link. Ewan is also a co-Chair of DCFW's Design Review panel. He was born and grew up in Wales.
Fiona is Head of Estates Projects at Swansea University. After graduating from the Welsh School of Architecture, she spent several years in private practice in Glasgow working primarily on research facilities for the HE Sector. She joined Swansea University in 1994. In her current role, she manages a complex programme of projects across the University estate. Fiona is a strong advocate of collaborative working across the construction industry, and has extensive experience of procuring and managing consultant and contractor frameworks.
An architect and urban designer, based in North East Wales, Trevor has wide experience of public sector work, including periods as Head of Architecture in Birmingham and City Architect in Newcastle.
Design Review panel members are all practicing professionals, experienced in all kinds of development.
Design Review panelists are appointed via competitive interview for a term of two years, pending review and reappointment. Panel members are unpaid. The panel is multi-disciplinary, reflecting the disciplines of urban and landscape design; architecture: buildings, structures and infrastructure; sustainability; planning; civil engineering; energy and transport infrastructure. They are individuals with significant reputations for excellence in their field.


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Machi Takahashi, cofounder and co-CEO of Stroly
Path finder: Machi Takahashi maps the interactive era
Oct. 7, 2019	06:55 am JST	 Oct. 7, 2019 | 06:55 am JST
By John Amari for The ACCJ Journal
When entrepreneur Machi Takahashi made the transition from executive assistant to business development at a research institute, she could not have imagined the move would lead to her creating a spin-off company.
Yet, as cofounder and co-CEO of Stroly, a free platform for sharing GPS-enabled designed maps, that is exactly what she has done.
Established 13 years ago, Stroly is an award-winning, series-funded startup with an expanding footprint in Japan, France, and the United States. At the same time, the company is creating waves on the tech scene in Japan and abroad.
Earlier this year, Stroly was the only representative from Japan at the pitch contest at South by Southwest (SXSW), a film, interactive media, and music conference and festival held annually in Austin, TX. The startup won first prize in the Entertainment and Content category.
Takahashi, meanwhile, has become a much-sought-after founder in Japan and abroad. This year, Forbes Japan included her on their Self-Made Women 100 list of leading women entrepreneurs.
ART AND TECH
Born in Yokohama but raised in Osaka, Takahashi was a sixth grader when she and her family relocated to New York. In hindsight, the move would lead to her lifelong love for the arts—a passion that, later on, moved her to establish Stroly.
For a Japanese child growing up in New York—and who could not speak English fluently—visiting local museums was one of her most-frequent, and safest, activities.
After returning to Osaka for high school, Takahashi made her way back across the Pacific after graduation. She attended Carleton College, a liberal arts school in Northfield, MN, where she majored in art history.
"Attending a school like Carleton College, I was always being asked, 'What do you really want to do? What's your real interest?' After two years of college, I really got into visual language—history of art really visualizes the whole history of culture. I also had the opportunity to be an intern at the Art Institute of Chicago, which was really cool."
The experience at Carleton College and the Art Institute of Chicago was inspiring. But what Takahashi was really interested in was the intersection of traditional arts and state-of-the-art technology. Shortly after graduation, and desiring to learn more about the tech industry, she joined an IT startup in Osaka.
"I was used to working with traditional arts that are locked away in museums, but I wanted to go into the world of the internet," she explained.
Soon after she joined the startup, she made another change. Almost on a whim, she joined the Advanced Telecommunications Research Institute International (ATR), an organization based in Kyoto. ATR conducts advanced research in such fields as life sciences, robotics, and telecommunications.
At first, she worked as an assistant to ATR's president. But when the opportunity arose to join the organization's newly established business development division, she took it.
"ATR had a section that spun off basic technology into businesses. So, I volunteered to be one of the people converting their seed technologies into commercial products."
MEETING OF MINDS
Those early days in ATR's business development unit were challenging for Takahashi. But the experience allowed her to pursue some of her earliest passions—bringing together art and technology.
Tasked with spinning off the fruits of ATR's research and development, Takahashi and her colleagues found it a struggle to bring the organization's nascent ideas to the market.
"We were very seed orientated back then, but, after trying a few things out, we became more customer focused and user interface oriented," she confessed.
With the new focus on users, Takahashi deployed ATR's tech based on artificial intelligence (AI) to suit the needs of clients, including museums in the Kansai region.
Such projects included creating an AI-powered recommendation service for museums. The service alerted visitors to artworks they may like based on their preferences of other works. That was in 2004 and 2005.
"That's when we came up with the idea of Stroly, which was established as a 100-percent-owned subsidiary of ATR."
Takahashi became Stroly's co-CEO and cofounder, together with Toru Takahashi, an expert in information engineering. A married couple, they met when both worked at ATR and are a rare example of a husband-and-wife team at the helm of a tech startup.
BREAKING GROUND
With its first iteration created in the pre-smartphone era, Stroly initially built a reputation for creating art-recommendation and guidance systems for galleries, museums, and amusement parks.
At the time, handheld personal digital assistants (PDAs), the PlayStation Portable video game console, and the Nintendo DS game system were all the rage, Takahashi recalled.
Such devices, she explained, included embedded web browsers. Using Wi-Fi, users could gain access to maps and guides powered by Stroly on their PDA.
"We were doing something very edgy for its time," she said.
It was in that period that the company created a guidance system for a theme park—but with an important innovation: their system had GPS positioning for illustrated maps.
"Many people probably use Google Maps to go from point A to B. But if you want to find richer, more detailed information, you probably look for other maps, such as those you get at the tourism office.
"But, using such maps, it's really hard to find your precise location. The Stroly platform helps you locate your position on these," Takahashi said. "And this technology of enabling GPS on any map of any form is very difficult to make. A lot of companies have tried and failed."
Stroly's technology transforms well designed but information-poor and inanimate maps into information-rich and engaging platforms. Companies such as real estate agents or train service operators can use the information gathered on the Stroly platform to gain a deep degree of insight into customer behavior when on their sites.
With a proof of concept and several patents in hand, Stroly was able to secure funding from government and other sources, allowing the startup to develop the platform. In 2016, the spinoff became independent of ATR, Takahashi and her cofounder having bought out the company and its intellectual property assets.
Stroly's, whose trade name is derived from the words stroll and story, has offices in Tokyo and Kyoto, as well as the United States and France.
The platform does more than simply produce engaging, data-rich, interactive maps. Users can upload any number of maps to Stroly, including historical maps, those of movie locations, or guides to local craft beer providers.
You can also locate your real-time position on any such map, or share your journey—including text or video memos—with others through social media.
For Takahashi, this is a game-changer. "The platform is fun, because it's not just a regular map that gives you information. Our maps have hand-picked, curated information. And you can actually enjoy how someone views the world."
So, it's not surprising that companies in the travel and leisure world, quite apart from real estate, transport and other industries, are beating a path to Stroly's front door in a bid to collaborate.
"Our customers are interested in things like area branding, tourism, and events."
This year, for instance, the Stroly platform powered SXSW's official event map online, as well as other illustrated maps around the event's location in Austin.
STANDING STRONG
Stroly has more than 70 projects currently underway and about 50 corporate clients, including real estate agency Mitsui Fudosan Co., Ltd., transport company Keihan Electric Railway Co., Ltd., and travel agency JTB Corporation.
The startup is clearly on a path to success. Looking back, can Takahashi recall a time when the going got tough? She can.
Around 2009, when Stroly was still under the auspices of ATR, there was an expectation from the parent company that other seed projects were to be prioritized.
"I had to fight against that, and I had to prove that this was a better idea than the one they come up with. So that was hard. We had to do a lot of in-house adjustments."
And with funding from the parent company drying up, and not being able to raise funds externally while still under the umbrella of a research institute, Takahashi felt that she needed help to make decisions about a way forward.
To that end, she joined Silicon Valley-based accelerator Women's Startup Lab (WSL), a project to support female founders. WSL was established by Japanese entrepreneur Ari Horie.
"I attended their two-week acceleration program in 2015, and was able to speak with a number of successful mentors. They had really good advice and feedback about our platform, including how I should grow it."
Equally important, Takahashi received expert advice on financing, business models, and scaling while at WSL. When she returned to Japan, she and her cofounder were in a position to make a decision—and that's when they decided to buy out the startup and go it alone.
Custom Media publishes The ACCJ Journal for the American Chamber of Commerce in Japan.
https://journal.accj.or.jp/path-finder/
© The ACCJ Journal
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text:
Axfood Närlivs var ett rikstäckande marknadsbolag som bedrev grossistförsäljning av dagligvaror till hela servicehandeln med huvudkontor i Örebro. Axfood Närlivs affärsidé var "Vi gör det enkelt för våra kunder att göra bra affärer". De var en av de större grossisterna inom Svensk Servicehandel och bland kunderna kan noteras Pressbyrån, 7-Eleven, Shell, OKQ8, Preem, Emab samt Statoil. Företaget bildades genom en sammanslagning av Dagab Närlivs och delar av tidigare KIAB.

Axfood Närlivs ingår sedan år 2000 i Axfoodkoncernen. Samma år genomfördes ett namnbyte från Dagab Närlivs. Tempo, Handlar'n och Direkten är fristående handlare som samarbetade med Axfood Närlivs under respektive varumärke. Den 31 december 2017 upplöstes Axfood Närlivs som aktiebolag, för att från den 1 januari 2018 bli ett affärsområde inom Dagab.

Historik
Dagab Närlivs bildades år 1997 genom sammanslagning av Dagab Servicehandel och delar av KIAB-koncernen. Ledningen låg inledningsvis i Stockholm, men flyttade efter 1999 till Örebro.

År 2000 bildades Axfood och företaget bytte namn till Axfood Närlivs. Man integrerade samtidigt Spar Inn Snabbgrossar.

Verkställande direktör
 1997–2000: Björn Abild
 2000–2005: Urban Dahl
 2005–2009-07-30: Benny Hast
 2009-08-01: Nicholas Pettersson
 2014-04-03: Eva Pettersson

Referenser

Noter

Källor
 Pressmeddelande 2014-04-03

Externa länkar
Officiell webbplats

Svenska dagligvaruhandelsföretag
Svenska partihandelsföretag
Företag i Stockholms kommun
Närlivs
Svenska butikskedjor


Some students don't follow oral directions well. There are several things you can do for such students.
One thing you can do is to stand directly in front of or close to the student whenever you give directions. Another thing you can do is to have the student sit in the front center of the classroom.
If feasible, use a signal that you are about to give directions, such as quickly turning the lights on and off. As a matter of course, check to see that the student's hearing has been checked recently.


text:
1964-09-16 - Three Years Ago
Summary: Three years ago, John Constantine met Lindon Mills in a mental institution.
It's a small, private medical facility, but it does handle the harder cases, and there's a hard case that arrived just a couple days ago. A man was struck by lightning, was in a coma for eight days, then woke up babbling in old languages and uttering fantastical things about demons and dark gods. They figured giving him a roommate might help him come around. Exposure to the world around him, and all that. It's not so great for his roommate. Poor John Constantine. His luck just isn't good.
The guy will not shut up. He won't eat, they can barely get him to take water. He's thin. So thin, and tall so he looks thinner still. He has a trembling fever sweat, dark hair clinging to his forehead and temples. His large dark eyes are haunted, darting back and forth like someone reading a page, only it's the empty air he scans.
Daemonium somniabunt. Non captures. Interfectus est. Over and over. Incessant.
Constantines luck was fucking non-existent and still, in spite of his best efforts to the contrary, the wanker somehow thrived. The tall blond Brit rolled over in his cot. What the hell, he wasn't getting any sleep anyways, but the constant prattling was just driving him batty The idea of coming here was to get better. The point was to prove none of this was real. The prattling on about demons? Well it wasn't very helpful. Finally he cracked a bloodshot eye open, "Somnia vera sunt. Non licet verum sit somnia." Latin he could argue in all day. He sighed though and had some modicum of pity among the irritation. "Let it go, mate. Just for a few hours. I need the sleep and you sure bloody well can at that."
"In hanc ergo perveniens. Occisio. Verus somnium. Greenwich Village. Nolite ire." He exhales softly, and his gaze stops scanning thin air. "Hello, John Constantine. Periculum est somnium. His fingers twitch at his sides, his body held so rigid it has to hurt. Auffere vult. Auffere vult. Auffere vult. His eyes close, probably for the first time in days, and his features twist in pain. Cerebrum nocet. Non possum accipere eam! He starts to thrash. Uh oh. this can't be good.
Constantine was tired but he knew what he heard. Slooooowly his eyes opened and where he was tired was chillingly wide awake. Dark brown irises that stained the glassy road maps of eyes stared at his roommate.
Quietly he whispered, "What… did you say there, mate?" Could they have spoken of him? Sure it was possible. Everything was possible, but that it was happening felt too coincidental to him and he knew too much to believe in coincidences.
Lindon tries to touch his head, but he's been restrained. For the thrashing, and also because when his hands were free he clawed at his head and there are still red marks in places. So it's a restrained thrashing, and his voice breaks as he yells in English, "Help me! Help me! Get it out of me!" Then he goes still, panting for breath. Weary, his voice aches with tiredness, helpless desperation. "You're not mad. It's real. It's all real." There's still nothing of clarity in his eyes, but his voice is so much more conversational.
Constantine pushed himself up and swung his feet over the edge landing on the tile floor with a smack. He'd seen quite a bit in his day from smack to possession and this seemed like it landed somewhere in the middle. In two steps he was across the room. Briefly he checked the hall and leaned close peering into Lindon's eyes. At Lindon's raving his expression looked wary with the offhanded comment, "Coming from another inpatient that's wildly reassuring." John sucked in his cheeks and then finally relented pressing the flat of his fingers to Lindon's forehead. "Get what out of you, give us something to go on, yeah?" It was encouraging at least if not clinical looking at the puzzle before him.
Lindon trembles. Restrained, he couldn't stop John if he tried. Just how aware is he of the man's presence? Enough to speak his name. At first he stares past Constantine, but then his focus returns, and it's sharp as a rapier, his gaze boring into John. "Everything," he whispers. "You don't understand, he put everything in there. It's all words, words whipping around, I don't I don't I don't know. I don't know what I am." He jerks violently at his restraints. "I saw and heard, and knew at last the How and Why of all things, past, and present, and forevermore. The Universe, cleft to the core, lay open to my probing sense that, sick'ning, I would fain pluck thence but could not,nay! But needs must suck at the great wound, and could not pluck my lips away till I had drawn all venom out.Ah, fearful pawn!" He tries to close the distance between John and himself, but he cannot. "For my omniscience paid I toll in infinite remorse of soul."
Constantine looked around and checked to see if the screaming was alerting the orderlies. On the upshot? Lindon was always screaming so this was not new. He pushed the sleeves up on his unbuttoned dress shirt that was crumpled and slept in more than once. He slapped his hands together and rubbed them togehter. He stood and cleared his mind and fixed his eyes on Lindons as he intoned the words "I am addressing the entity inside… Who are you?" Hey, it was worth a shot if he was possessed.
Now that's a tricky question. It's enough to make Lindon stop thrashing. He lies still, panting for breath. His voice is suddenly quiet. Somewhat retiring, really. "I'm the Archive. I'm…" His brow furrows. "I'm a tree." The orderlies and nurses who haven't called him Mr. Mills have called him Lindon. That's a kind of tree, more or less. "Tilia Americana, ranged from southern Canada as far south and west as Oklahoma. Simple, alternately arranged leaves, ovate to cordate, asymmetrical at the base. In spring, it produces yellowish-white flowers that smell like semen." So a linden. What a thing to be named after.
Okay, not what he was expecting. Hmmm. He held his hands out over over this 'Archive' hesitantly. A tongue ran over his bottom lip and he sighed, "You might be confirming I lost my marbles, Lindon-tree, but why the bloody hell not go out with a bang." His hands snapped over Lindon who was already secured to his cot and intoned "In nomine Sancte Luca, Sancte Marce, Raziel Et angelus, quem ostendit mihi videntur!" This was, perhaps, a spectacularly bad idea.
Lindon's back arches and he cries out, "In nomine Sancte Luca, Sancte Marce, Raziel Et angelus, quem ostendit mihi videntur!" his voice breaks. "It hurts. I can't do this. No, no, no, pick someone else." Something in what Constantine has done causes a shift. Lindon's features start to form an expression. It's anguish. Pain. "It's too much," he says, taking ragged breaths. "I can't shut it up. I can't stop thinking."
Constantine set his haw and tilted his head askew. Something was off. Lindon wasn't possessed by a spirit. This was something else something…older? Veeeeeeery curious, and whatever it was spilling out where knowledge was concerned it was seeping out like a radium clock leaked radiation. With jaw still clenched John gave the article inside Lindon or that was Lindon such a stare down and with that pushed up his sleeves, anchored himself, and focused his will through every tightened muscle in his body. The words bellowed over LIndon's cries //"Raziel, custos sapienti%<230>, lux autem scientiam, librum mentis Tuae aciem perstringere. Consuendi a tergo paginae intra numine Parcae.
Constantine set his haw and tilted his head askew. Something was off. Lindon wasn't possessed by a spirit. This was something else something…older? Veeeeeeery curious, and whatever it was spilling out where knowledge was concerned it was seeping out like a radium clock leaked radiation. With jaw still clenched John gave the article inside Lindon or that was Lindon such a stare down and with that pushed up his sleeves, anchored himself, and focused his will through every tightened muscle in his body. The words bellowed over LIndon's cries "Raziel, custos sapienti%<230>, lux autem scientiam, librum mentis Tuae aciem perstringere. Consuendi a tergo paginae intra numine Parcae." The risk wasn't even just to LIndon but everyone around him as well and if he was innatly familir with anything? It was collatoral damages.
Sometimes, just sometimes, luck doesn't bend over Constantine and spread its cheeks. Sometimes, luck decides to toss him a bone. See, the facts are these: that thing inside Lindon is crushing him. It's going to kill him if it keeps boring into him the way it's doing now. To keep him alive, something vastly bigger than he is needs to be crammed into an itty bitty living space.
Who better to call on than the angel of wisdom and knowledge? There's a rosary on the table beside Lindon's bed. He might well be Catholic. Fitting. He starts shaking, but this time it's the bed, not his body. It rattles in its frame, scraping on the floor. The lights dim and flicker, and the tang of magic in the air is palpable. Lindon screams. No words this time. Just a scream of anguish. Is he even going to survive this? Oops if he doesn't, right?
Then he collapses, silent, panting for breath. Breathing is good. Even if he winces with each breath. The patter of footsteps draw closer. Someone's coming to check on them.
Orderlies were drawn in my John's yelling with Lindon's and the inevitable rattling of furniture. Two of the three orderlies rushed in to see John standing over Lindon yelling at him and did what good professionals do; they tackled him to the floor. There was a grunt and immediate protests, "Don't touch him, he's fine everything- Shite!" Oh being subdues was never fun and often painful and… they were trying to drag him from the room. He yelled back, "His pulse, check his pulse! Lindon? Bloody hell, Lindon! Let go of me you bloody wanker and see he's alright!"
One of the orderlies chastises John. "You'll watch your language here, Mr. Constantine." She's not the big burly man that's twisting John's arms behind his back with a knee in the small of his back. No, she's the one coming over to Lindon, whose bed is being held still by another couple of big guys. It starts to settle down of its own accord. One of the nurses comes over to the bedside takes Lindon's pulse at his wrist.
When she touches Lindon, his eyes fly open and he gasps, trying to sit up, but the restraints pull him back to the bed. "I'm okay," he says. "I'm okay. I'm okay. I…" He looks around, clammy like a guy whose fever just broke but he still looks like hell. "Who am I?" He blinks at John without a lick of recognition. "Who's he?"
Constantine says, "He's" he coughed, "a man in need of a whiskey sour. Don't mine me, mate." He glanced a look up to the orderly subduing him and he couldn't help but answer the chastising with a wry grin, "I think you've done this before. You know I happen to be free later, luv?" And that was a knee to his lower back that was met with a groan. "Whaaat I'm complying! That was a compliment. a compliment!" It hurt is what it was. He winced and took a deep breath and just lay there defeated, and partially slack-jawed. On one hand he was purely amazed by what he was looking at; a great, grand puzzle. On the other hand this meant his entire trip to the asylum was a total waste of time. "I'll tell you it's been a blast, but apparently I am," not a namegive, "leaving in the morning."
Lindon tries to sit up again, but the nurse soothes him back and the orderlies stand by in case this maniac breaks free and needs to be tackled. Which in this case he does not. Lindon lies back, and he says, "He wasn't hurting me. I don't think so? My… my head hurts. I think I might need to throw up." Because the mother of all migraines will do that to a man. But hey, he did stand up for John in all this even as his head feels like it's splitting open.
Constantine was still on the floor. Of all the times he's wound up on strange floor this wasn't even ranks among his least favourite. That he had a list should concern people. That bar in Bristol? Oddly still leading for worst situation where he wound up face down on a floor. Right now calm would buy him out of a very literal bind though. His eyes, dark brown and full of haunted wonder, curiously observed Lindon gaining cohesiveness. He could see the runes of will binding his way into him. He murmured to himself, "Thaaaat's a good book." Finally they pulled him to his feet. "Satisfied? I'll thank everyone if I could jut get some bleedin sleep."
"I'm tired," Lindon observes on the tail end of John saying he'd like to get some sleep.
The nurse takes his vitals, and she jots down notes. "Do you think you can sleep without a sedative Mr. Mills, or do you need some help?"
Lindon shakes his head and says quietly, "I'm already falling asleep." It's been three days without real rest. "Something for the pain, though…" The binding hurts, but he'll live. And it'll be bloody quiet enough for John to get some rest. The orderlies and nurse begin to file out of the room, the latter to get some morphine for her aching patient.
Constantine was at least relieved to hear that. He offered to the nurse, "A drink will likely help." She apologized and informed, "We are not giving him alcohol, Mr. Constantine."
John scoffed, "Not for him for me. You help a bloke out and you can't even get a pint for it anymore? This world is burning." He shook his head and dropped back down into his bed lazily sprawling out on it with one forearm over his eyes, "Cheers, mate." And with that he finally go some goddamned sleep.
By morning though, true to his word, John Constantine was checked out. This time in a literal and geographic sense.
_importedconstantinelindonsocial