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Despite recent advances in face recognition using deep learning, severe accuracy drops are observed for large pose variations in unconstrained environments. Learning pose-invariant features is one solution, but needs expensively labeled large-scale data and carefully designed feature learning algorithms. In this work, we focus on frontalizing faces in the wild under various head poses, including extreme...
Facial alignment involves finding a set of landmark points on an image with a known semantic meaning. However, this semantic meaning of landmark points is often lost in 2D approaches where landmarks are either moved to visible boundaries or ignored as the pose of the face changes. In order to extract consistent alignment points across large poses, the 3D structure of the face must be considered in...
Deep neural networks (DNNs) trained on large-scale datasets have recently achieved impressive improvements in face recognition. But a persistent challenge remains to develop methods capable of handling large pose variations that are relatively under-represented in training data. This paper presents a method for learning a feature representation that is invariant to pose, without requiring extensive...
In this paper we present a novel approach for 3D facial expression recognition based on a registration method. The used registration method, called the Coherent Point Drift (CPD), is applied to estimate complex non-linear and nonrigid transformation between 3D facial surfaces. The computed transformation allows to recover shape deformations that are induced by facial expression variations. Machine...
In modern days the demand for biometrics increases rapidly. The world still needs to solve many problems and answer to lot of questions regarding to biometrics for creating better solutions for recognition and verification of objects. Biometrics has become really important topic of our security. Number of input samples per person affects recognition in modern algorithms used for face recognition....
Pose and illumination are considered as two main challenges that face recognition system encounters. In this paper, we consider face recognition problem across pose and illumination variations, given small amount of training samples and single sample per gallery (a.k.a., one shot classification). We combine the strength of 3D models in generating multiviews and various illumination samples and the...
Automatic face recognition has been integrated in many systems thanks to the improvement of face comparison algorithms. One of the main applications using facial biometry is the identity authentication at border control, which has already been adopted by a lot of airports. In order to proceed to a fast identity control, gates have been developed, to extract the ID document information on the one hand,...
Face analysis is a challenging topic, especially when addressing low-resolution data. While face detection is working satisfactorily on such data, further facial analysis often struggles. We specifically address the issues of face registration, face normalization and facial feature extraction to perform low-resolution face recognition. For face registration, an approach for landmark detection, pose...
The deployment of cameras for security control allows for video stream to be used as input for face recognition (FR). However, most state of the art FR SDKs are generally specifically tuned for dealing with frontal and neutral face images, whereas expression and pose variations, which typically occur in unconstrained settings, e.g., video images, are still major challenges for reliable FR. In this...
In this paper we address the problem of pose independent face recognition with a gallery set containing one frontal face image per enrolled subject while the probe set is composed by just a face image undergoing pose variations. The approach uses a set of aligned 3D models to learn deformation components using a 3D Morph able Model (3DMM). This further allows fitting a 3DMM efficiently on an image...
With the rapid development of range image acquisition techniques, 3D computer vision has became a popular research area. It has numerous applications in various domains including robotics, biometrics, remote sensing, entertainment, civil construction, and medical treatment. Recently, a large number of algorithms have been proposed to address specific problems in the area of 3D computer vision. Meanwhile,...
In this paper, we propose an efficient method to reconstruct the 3D models of a human face from a single 2D face image robustness under a variety facial expressions using the Deformable Generic Elastic Model (D-GEM). We extended the Generic Elastic Model (GEM) approach and combined it with statistical information of the human face and deformed generic depth models by computing the distance around...
One of the major challenges encountered by face recognition lies in the difficulty of handling arbitrary poses variations. While different approaches have been developed for face recognition across pose variations, many methods either require manual landmark annotations or assume the face poses to be known. These constraints prevent many face recognition systems from working automatically. In this...
There are several types of spoofing attacks to face recognition systems such as photograph, video or mask attacks. Recent studies show that face recognition systems are vulnerable to these attacks. In this paper, a countermeasure technique is proposed to protect face recognition systems against mask attacks. To the best of our knowledge, this is the first time a countermeasure is proposed to detect...
Recently, there has been an increasing interest in using 3D facial images as biometric modality. To that end, a proper representation of the 3D facial shape that would allow effective face matching is a major requirement. In this paper, we propose a novel 3D facial representation, dubbed, the face-tree. We describe the extraction process of this representation from 3D triangular mesh face model, then...
In this paper we present a fully automatic approach for identity-independent facial expression recognition from 3D video sequences. Towards that goal, we propose a novel approach to extract a scalar field that represents the deformations between faces conveying different expressions. We extract relevant features from this deformation field using LDA and then train a dynamic model on these features...
This survey addresses methodologies for 3D mesh video retrieval including 3D mesh video action/motion retrieval and 3D mesh video facial expression recognition. They all involve retrieval procedures and, consequently, classification methods in order to identify similar actions/motions and facial expressions. The approaches are primarily categorized according to the 3D model representation that they...
3D face modeling from 2D face images is of significant importance for face analysis, animation and recognition. Previous research on this topic mainly focused on 3D face modeling from a single 2D face image; however, a single face image can only provide a limited description of a 3D face. In many applications, for example, law enforcement, multi-view face images are usually captured for a subject...
Existing work of 3D morphable models mainly focuses on 3D face recognition and reconstruction but ignores the ear regions which are usually captured together with the face images. However, ears are almost rigid structures, which are relatively stable to age growth and resist the facial expression variations, making themselves an effective supplement of faces for personal identification. Hence, we...
Over the past decades, 3D face has emerged as a solution to face recognition due to its reputed invariance to lighting conditions and pose. While proposed approaches have proven their efficiency over renowned databases as FRGC, less effort was spent on studying the robustness of algorithms to quality degradations. In this paper, we present a study of the robustness of four state of the art algorithms...
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