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In this paper, we proposed a new technique for facial expression recognition based on extraction of Complete Robust Local Binary Pattern (CRLBP) features from curvelet domain. The curvelet transform show evidence of improved multiscale directional capability, and a greater ability to localize distributed discontinuities such as edges along curves as compared to traditional multiscale transform such...
Derivation of discriminant features from outstanding face patches has a major role in accurate identification of face expressions. The precise discovery of fragments in the face image improves the confinement of the outstanding patches on face images. Some methods uses a special framework for expression identification by the use of appearance related features of important face patches. A few noticeable...
Recognition under uncontrolled lighting conditions remains one of the major challenge for practical face recognition systems. In this work, we present an efficient and effective framework to improve the recognition performance from two aspects: image preprocessing and subspace representation. The step of image preprocessing is mainly used to eliminate the effects of illumination. The step of subspace...
We propose a novel and general framework, named the multithreading cascade of rotation-invariant histograms of oriented gradients (McRiHOG) for facial expression recognition (FER). In this paper, we attempt to solve two problems about high-quality local feature descriptors and robust classifying algorithm for FER. The first solution is that we adopt annular spatial bins type HOG (Histograms of Oriented...
With the prevalence of camera networks, multi view surveillance video have become commons. Multi view face recognition has become an active research area in recent years. In this paper, an approach for video-based face recognition in camera networks is proposed. Video scenes have unlimited orientation and poses. Video provide an efficient way for feature extraction. The proposed feature is developed...
Face recognition has been largely studied in past years. However, most of the related work focus on increasing accuracy and/or speed to test a single pair probe-subject. In this work, we present a novel method inspired by the success of locality sensing hashing (LSH) applied to large general purpose datasets and by the robustness provided by partial least squares (PLS) analysis when applied to large...
In this paper, the Radio-frequency identification (RFID) technology and face recognition are integrated for access control system. A rapid face detection scheme which using a set of rotated haar-like features is adopted for face detection. A normalization process is then applied to adjust the detected faces. The speeded up robust features (SURF) algorithm is used for registering the detected face...
In hyerspectral image analysis, representation-based classification is a novel concept — a testing pixel is linearly represented by using the labeled samples. The weight coefficients can be solved by an ℓ1-norm penalty for sparse representation, or solved by an ℓ2-norm penalty for collaborative representation. In this work, a convex combination of these two representations using the elastic net model...
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...
Metric learning has attracted increasing attentions recently, because of its promising performance in many visual analysis applications. General supervised metric learning methods are designed to learn a discriminative metric that can pull all the within-class data points close enough, while pushing all the data points with different class labels far away. In this paper, we propose a Discriminative...
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...
In this paper, we propose a patch based face recognition framework. First, a face image is iteratively divided into multi-level patches and assigned hierarchical labels. Second, local classifiers are built to learn the local prediction of each patch. Third, the hierarchical relationships defined between local patches are used to obtain the global prediction of each patch. We develop three ways to...
In this paper, we design a Collaborative-Hierarchical Sparse and Low-Rank (C-HiSLR) model that is natural for recognizing human emotion in visual data. Previous attempts require explicit expression components, which are often unavailable and difficult to recover. Instead, our model exploits the low-rank property to subtract neutral faces from expressive facial frames as well as performs sparse representation...
India holds one of the largest domains of the world in providing governance within a population of 1.2 billion people. Recent years have seen massive initiatives from all sides for using inclusive technology in catering public services. Several ventures like 'digital India' have been taken to improve the inbuilt technology in different governance systems. But ageing systems and isolated service-domains...
With the prevalence of camera networks, multi view surveillance video have become commons. Multi view face recognition has become an active research area in recent years. In this paper, an approach for video-based face recognition in camera networks is proposed. Video scenes have unlimited orientation and poses. Video provide an efficient way for feature extraction. The proposed feature is developed...
Mobile devices (laptops, tablets, and smart phones) are ideal for the wide deployment of biometric authentication, such as face recognition. However, their uncontrolled use and distributed management increases the risk of remote compromise of the device by intruders or malicious programs. Such compromises may result in the device being used to capture the user’s face image and replay it to gain unauthorized...
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,...
This paper proposes a combined approach for robust face recognition from low resolution images captured by a low-budget commercial depth camera. The low resolution of the facial region of interest is compensated via oversampling techniques and efficient trimming algorithms for the generation of an accurate 3D facial model. Two state of the art algorithms for geometric feature extraction are then utilized,...
A novel and robust biometric face identification algorithm for access control applications is proposed. The key contribution is the design of a high discriminative feature descriptor for depth imagery, called Depth Spatiogram of Local Quantized Patterns, which is used as input of a bank of Support Vector Machine classifiers.
Programmed Face Identification (PFI) of images more reliable even under unstable lighting conditions is one of the most important challenges for practical face recognition systems. We tackle this by combining the strengths of robust illumination normalization, local texture-based face representations, distance transform based matching, multiple feature fusion. Additionally we propose Phase Congruency...
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