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The way to extract facial expression features from 3D face image is significant in 3D expression recognition. However, most of the feather extraction methods are based on geometric. In this paper, we extend a combined strategy for Local Binary Patterns (LBP) and Supervised Locality Preserving Projection (SLPP) in facial expression recognition. First, we use LBP to get the histogram of the image. Then...
For benefiting from incorporating the class information, partial least squares (PLS) and its two dimension version (2DPLS) have been widely employed in face recognition when extracting principal components. However, currently popular statistic methods, such as principal component analysis (PCA) and linear discriminant analysis (LDA), only learn holistic, not parts-based, representations which ignore...
This paper addresses the problems of feature selection and feature fusion. For the feature selection, the color SIFT descriptors in the independent components are ordered for image classification. To select distinctive and compact independent components (IC) of the color SIFT descriptors, we propose two ordering approaches based on variation: (1) Local ordering approaches (the localization-based ICs...
We develop a framework based approach to extract and recognize hand gestures from the video sequence acquired by a dynamic camera, which could be a useful interface between humans and mobile robots. We use Human-Following Local Coordinate (HFLC) System, a very simple and stable method for extracting hand motion trajectories, which is obtained from the located human face and body part. Hand trajectory...
Face occlusion is a common problem that occurs in applications that analyze images for faces, e.g. detection, tracking and recognition. The presence of occlusion can adversely affect such face processing algorithms. This paper proposes a solution to the problem: we attempt to remove the occlusion by considering it as a damaged part that needs to be regenerated. More precisely, our technique learns...
In this paper, a novel palmprint recognition approach is presented. A modified discrete cosine transform based feature extraction method is used to obtain palmprint features. Furthermore, a radial basis function neural network is employed for palmprint classification. In order to facilitate the training of radial basis function neural network, principal components analysis is applied to reduce these...
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