We present a novel discriminative regression based approach for the Constrained Local Models (CLMs) framework, referred to as Discriminative Response Map Fitting (DRMF) method, which shows impressive performance in generic face fitting scenario. The motivation behind this is that, unlike holistic texture features used AAM approaches, response map can be represented by small set of parameters and these very efficiently reconstructing unseen maps. Furthermore, we show that adopting simple...

The development of facial databases with an abundance annotated data captured under unconstrained 'in-the-wild' conditions have made discriminative deformable models the de facto choice for generic landmark localization. Even though very good performance localization has been shown by many recently proposed techniques, when it comes to applications that require excellent accuracy, such as behaviour analysis and motion capture, semi-automatic person-specific or even tedious manual tracking is...

Recently proposed robust 3D face alignment methods establish either dense or sparse correspondence between a model and 2D facial image. The use of these presents new challenges as well opportunities for texture analysis. In particular, by sampling the image using fitted model, UV can be created. Unfortunately, due to self-occlusion, such map is always incomplete. this paper, we propose framework training Deep Convolutional Neural Network (DCNN) complete extracted from in-the-wild images. To...

In recent years, researchers have intensively investigated various topics in test prioritization, which aims to re-order tests increase the rate of fault detection during regression testing. While main research focus prioritization is on proposing novel techniques and evaluating more larger subject systems, little effort has been put investigating threats validity existing work prioritization. One threat that mainly evaluates based simple artificial changes source code tests. For example,...

The progress we are currently witnessing in many computer vision applications, including automatic face analysis, would not be made possible without tremendous efforts collecting and annotating large scale visual databases. To this end, propose 4DFAB, a new database of dynamic high-resolution 3D faces (over 1,800,000 meshes). 4DFAB contains recordings 180 subjects captured four different sessions spanning over five-year period. It 4D videos displaying both spontaneous posed facial...

Abstract This paper presents a novel approach for synthesizing facial affect; either in terms of the six basic expressions (i.e., anger, disgust, fear, joy, sadness and surprise), or valence how positive negative is an emotion) arousal power emotion activation). The proposed accepts following inputs:(i) neutral 2D image person; (ii) expression pair valence-arousal (VA) emotional state descriptors to be generated, path affect VA space generated as sequence. In order synthesize VA, this...

Mutation testing is a powerful methodology for evaluating test suite quality. In mutation testing, large number of mutants are generated and executed against the to check ratio killed mutants. Therefore, widely believed be computationally expensive technique. To alleviate efficiency concern in this paper, we propose predictive (PMT), first approach predicting results without mutant execution. particular, proposed constructs classification model based on series features related tests, uses...

Micro-expressions (ME) are a special form of facial expressions which may occur when people try to hide their true feelings for some reasons. MEs important clues reveal people's feelings, but difficult or impossible be captured by ordinary persons with naked-eyes as they very short and subtle. It is expected that robust computer vision methods can developed automatically analyze requires lots ME data. The current datasets insufficient, mostly contain only one single 2D color videos....

Estimating the 3D facial landmarks from a 2D image remains challenging problem. Even though state-of-the-art alignment methods are able to predict accurate for semi-frontal faces, majority of them fail provide semantically consistent profile faces. A de facto solution this problem is through face that preserves correspondence across different poses. In paper, we proposed Cascade Multi-view Hourglass Model alignment, where first model explored jointly and landmarks, after removing spatial...

Generative Adversarial Networks (GANs) are currently the method of choice for generating visual data. Certain GAN architectures and training methods have demonstrated exceptional performance in realistic synthetic images (in particular, human faces). However, 3D object, GANs still fall short success they had with images. One reasons is due to fact that so far been applied as convolutional discrete volumetric representations objects. In this paper, we propose first intrinsic architecture...

We propose a face alignment framework that relies on the texture model generated by responses of discriminatively trained part-based filters. Unlike standard models built from pixel intensities or generic filters (e.g. Gabor), our has two important advantages. First, virtue discriminative training, invariance to external variations (like identity, pose, illumination and expression) is achieved. Second, we show (or patch-experts) are sparse can be modeled using very small number parameters....

Semantic segmentation of eyes has long been a vital pre-processing step in many biometric applications. Majority the works focus only on high resolution eye images, while little done to segment from low quality images wild. However, this is particularly interesting and meaningful topic, as play crucial role conveying emotional state mental well-being person. In work, we take two steps toward solving problem: (1) We collect annotate challenging dataset containing 8882 patches 4461 facial...

Several factors contribute to the appearance of an object in a visual scene, including pose, illumination, and deformation, among others. Each factor accounts for source variability data, while multiplicative interactions these emulate entangled variability, giving rise rich structure appearance. Disentangling such unobserved from data is challenging task, especially when have been captured uncontrolled recording conditions (also referred as "in-the-wild") label information not available. In...

For real-time semantic video segmentation, most recent works utilised a dynamic framework with key scheduler to make online key/non-key decisions. Some used fixed scheduling policy, while others proposed adaptive methods based on heuristic strategies, both of which may lead suboptimal global performance. To overcome this limitation, we model the decision process in segmentation as deep reinforcement learning problem and learn an efficient effective policy from expert information about...

The uncommon metabolic pathways of organic pollutants are easily overlooked, potentially leading to idiosyncratic toxicity. Prediction their biotransformation associated with the toxic effects is very purpose that this work focuses, develop a de novo method mechanistically predict reactive toxicity metabolites from start aliphatic amine molecules, which employed sertraline triggered by CYP450 enzymes as model system, there growing concerns about on human health posed antidepressants in...

Abstract N-Nitrosamines are a class of compounds that includes the potent mutagenicity and carcinogenicity many its members is distributed widely throughout human environment. DNA alkylation by their diazonium ions formed metabolically acts as molecular initiating event (MIE) links chemistry to mutagenicity. However, regiochemistry for reacting with bases still under debate. Hence, density functional theory calculations involving SN2 guanine (Gua) 14 diverse presented, results which showed...

Robust principal component analysis (RPCA) is a powerful method for learning low-rank feature representation of various visual data. However, certain types as well significant amount error corruption, it fails to yield satisfactory results; drawback that can be alleviated by exploiting domain-dependent prior knowledge or information. In this paper, we propose two models the RPCA take into account such side information, even in presence missing values. We apply framework task UV completion...

The problem of fitting a 3D facial model to mesh has received lot attention the past 15–20 years. majority techniques fit general consisting simple parameterisable surface or mean shape. drawback this approach is that rather difficult describe non-rigid aspect face using just single model. One way capture deformations by means statistical its parts. This particularly evident when we want mouth region. Even though models are generally applied for modelling intensity, there few approaches...