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In this paper, with the help of controllable active near-infrared (NIR) lights, we construct near-infrared differential (NIRD) images. Based on reflection model, NIRD image is believed to contain the lighting difference between images with and without active NIR lights. Two main characteristics based on NIRD images are exploited to conduct spoofing detection. Firstly, there exist obviously spoofing...
It is a challenging problem to realize a robust and low cost gaze estimation system. Most existing feature-based gaze estimation methods strongly rely on cornea reflections, which are unstable to glasses, head movements and natural light. In this paper, we propose a novel gaze estimation method without use of cornea reflections based on a stereo camera system. Firstly, 3D Active Shape Models (ASM)...
A novel learning based framework for efficient heterogeneous faces synthesis is proposed. Based on the same spectral distribution of each modality, a statistical probability model is developed for the mapping learning problem between two groups of facial appearances, instead of the traditional linear regression model. Furthermore, in order to eliminate the influences of facial structure and spectrum...
Human skin detection in images is desirable in many practical applications, e.g., adult-content filtering. However, existing methods are mainly pixel-based and ignore that human skin is region-based. In this paper, we introduce a successful region detector, i.e., MSER, into the skin detection by regarding the skin region as the maximally stable extremal region (MSER). We extend the original MSER to...
In this paper, we propose a new algorithm for shape initialization and 3D pose alignment in Active Shape Model (ASM). Instead of initializing with average shape in previous works, we build a scatter data interpolation model from key points to obtain the initial shape, which ensures shape initialized around face organs. These key points are chosen from organs of face shape and located with a strong...
Many previous image processing methods discard low-frequency components of images to extract illumination invariant for face recognition. However, this method may cause distortion of processed images and perform poorly under normal lighting. In this paper, a new method is proposed to deal with illumination problem in face recognition. Firstly, we define a score to denote a relative difference of the...
This paper presents a new probabilistic local binary pattern (PLBP), an extension of existing local binary pattern (LBP), for face verification. Unlike LBP employing the sign of the difference to express the result of comparing two pixels, PLBP employs probability to express it. The advantage is that it can encode the magnitude of the difference, which is useful for face verification but is ignored...
This paper presents a novel algorithm for face recognition based on a single image and a new LBP (Local Binary Pattern) descriptor. The algorithm can be divided into three steps: firstly, calculating both the horizontal and vertical edge maps from the gray image; then extracting LBP histograms from those two edge images; finally, adopting elastic matching for classification. In addition, in order...
In this paper, a novel framework for face recognition based on discriminatively trained orthogonal rank-one tensor projections (ORO) and local binary pattern (LBP) is proposed. LBP is an efficient method for extracting shape and texture information and it is robustness to illumination and expression, while ORO has been successful in appearance based face recognition by finding orthogonal tensors....
This paper proposes an extension of marginal fisher analysis (EMFA) for dimensionality reduction and analyzes some properties of both EMFA and linear discriminant analysis (LDA), and finally suggests a synthesized discriminant projection (SDP). SDP takes both global class relationship and local geometry structure into account, which maximizes the distance between marginal points and the distance between...
Face recognition, which is an active research area in pattern recognition, has made great progress in recent years. Its performance that based on multiple face images is satisfying, but it is remain poor when only a single face image is used to training. Accordingly, we propose a new algorithm of face recognition that based on a single face image in this paper. The new algorithm can be divided into...
Face recognition algorithms have to deal with significant amounts of illumination and expression variations between gallery and probe images. This paper analyzes the facial image of multi-level wavelet decomposition features, points out the facts that illumination variations have the greatest impact on the low-frequency decomposition approximation coefficients, followed by expression and individual...
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