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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...
Nowadays, facial expression synthesis is widely used in expression simulation, recognition and animation. Texture feature (wrinkle) after face deformation largely reflects the genuineness of the synthesized expression, whose mapping is a critical step to the expression synthesis application. However, current lighting ratio based wrinkle mapping is sensitive to small source lighting and large lighting...
People are highly efficient in recognizing faces. However, it is almost impossible for them to cope with huge datasets of facial images without any computational support. On the other hand, the way people describe the facial features using quite commonly encountered descriptors such as “long nose”, “small eyes” and also allude to their feelings according to a specific person like “seems to be nice”,...
A solution to long distance outdoor face recognition is presented in this work. The proposed method, called the Two-Stage Alignment/Enhancement Filtering (TAEF) system, consists of three main components: a cross-distance face alignment technique, a cross-environment face enhancement technique, and a two-stage filtering system. Given a probe image, the procedure of face alignment, enhancement and matching...
Face Hallucination (FH) differs from generic single-image super-resolution (SR) algorithms in its specific domain of application. By exploiting the common structures of human faces, magnification of lower resolution images can be achieved. Despite the growing interest in recent years, considerably less attention is paid to a crucial step in FH -- registration of facial images. In this work, registration...
This paper proposes a novel local depth and surface normals descriptor to explore the discriminative features on the nasal surface and the adjoining cheek regions for expression robust 3D face recognition. After preprocessing the 3D face data, landmarks located on the perimeter of a triangular region covering the nose and adjoining parts of the cheeks are accurately detected. Inspired by Local Binary...
Gabor features have been used widely in face identification because of their good results and robustness. However, face identification is strongly affected when the test images are very different from those of the gallery, as is the case in varying face pose. In this paper, a new 2D Gabor-based method is proposed that modifies the grid from which the Gabor features are extracted using a mesh to model...
In this paper, we recognize the need of de-identifying a face image while preserving a large set of facial attributes, which has not been explicitly studied before. We verify the underling assumption that different visual features are used for identification and attribute classification. As a result, the proposed approach jointly models face de-identification and attribute preservation in a unified...
Nose tip localization is an important step for registration, preprocessing and recognition of 3D face data. In this paper, we propose a new approach for the nose tip detection that is robust to pose and expression variations and in presence of occlusions. From a rotated 3D face, we extract facial curves that are matched to a profile curve model. An optimal matching using the Riemannian geometry, based...
The classical curvatures of smooth surfaces (Gaussian, mean and principal curvatures) have been widely used in 3D face recognition (FR). However, facial surfaces resulting from 3D sensors are discrete meshes. In this paper, we present a general framework and define three principal curvatures on discrete surfaces for the purpose of 3D FR. These principal curvatures are derived from the construction...
Despite being increasingly easy to acquire, 3D data is rarely used for face-based biometrics applications beyond identification. Recent work in image-based demographic biometrics has enjoyed much success, but these approaches suffer from the well-known limitations of 2D representations, particularly variations in illumination, texture, and pose, as well as a fundamental inability to describe 3D shape...
Automatic face recognition across large pose changes is still a challenging problem. Previous solutions apply a transform in image space or feature space for normalizing the pose mismatch. For feature transform, the feature vector extracted on a probe facial image is transferred to match the gallery condition with regression models. Usually, the regression models are learned from paired gallery-probe...
This paper addresses the issue of automatic classification of the six universal emotional categories (joy, surprise, fear, anger, disgust, sadness) in the case of static images. Appearance parameters are extracted by an active appearance model(AAM) representing the input for the classification step. We show how Relevant Component Analysis (RCA) in combination with Fisher's Linear Discriminant (FLD)...
We propose in this paper, a gender recognition solution under the presence of occlusion and using the very restrict samples in the learning base. The developed approach is based on the extraction of pertinent 3D depth-radial curves that cover the nose region and combined dimensionality reduction using sparse random projection method; furthermore we propose an extension of similarity based classification...
Facial expression recognition plays a major role in non verbal communication. Recognition by machine is still a challenging problem. To automate the recognition for human machine interaction, a system is proposed in this paper. The proposed system uses shape descriptors to identify twelve land marks which mainly contribute to the facial expression recognition. From the location and the size or boundary...
One of the well-known problems of the face recognition is occlusion. Occlusion in an image refers to hindrance in the view of an object. The article aims to give a detailed survey of the face recognition under occlusion. Human face recognition under occlusion is broadly classified into 8 categories Karhunen-Loeve Expansion Method, Model Based Method, Correlation Based Method, Template Based Method,...
Facial expression is a way of non-verbal communication. A person depicts his/her feelings through facial expressions. In computer systems facial expressions help in verification, identification and authentication. One popular use of facial expression recognition is automatic feedback capture from customers upon reacting to a particular product. Effective recognition technology is in high demand by...
Face recognition is an important technique for Natural User Interface (NUI) and Human Robot Interaction (HRI) and many of the current state-of-the-art face recognition techniques are based on the local features which are extracted from a face alignment method like Constrained Local Model (CLM). But, in a real world environment, face alignment methods often fail to correctly localize the features because...
Facial expression recognition has many potential applications which has attracted the attention of researchers in the last decade. Feature extraction is one important step in expression analysis which contributes toward fast and accurate expression recognition. This paper represents an approach of combining the shape and appearance features to form a hybrid feature vector. We have extracted Pyramid...
In this paper we introduce a novel face representation method called Cross Local Binary Patterns(XLBP) to improve the robustness of face recognition for partially occluded and non-uniformly illuminated face images. In our method we use Radon transform to capture the coarse level shape information and XLBP to capture the texture information. Individual histograms computed on each sub-block of the face...
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