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Titlebook: Computer Vision - ACCV 2006; 7th Asian Conference P. J. Narayanan,Shree K. Nayar,Heung-Yeung Shum Conference proceedings 2006 Springer-Verl

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51#
發(fā)表于 2025-3-30 11:22:51 | 只看該作者
52#
發(fā)表于 2025-3-30 14:57:26 | 只看該作者
Fusion of Texture Variation and On-Line Color Sampling for Moving Object Detection Under Varying Chrthat utilize color information, the assumption of smooth or global change of illumination is no longer needed. Our method is based on the observation that the color appearance of objects may alter as the change of light intensity and color, but their texture structures remain almost the same. Theref
53#
發(fā)表于 2025-3-30 18:01:05 | 只看該作者
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發(fā)表于 2025-3-31 00:15:18 | 只看該作者
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發(fā)表于 2025-3-31 04:06:21 | 只看該作者
Occlusion Invariant Face Recognition Using Selective LNMF Basis Imageschnique. The proposed algorithm is composed of two phases; the occlusion detection phase and the selective LNMF-based recognition phase. We use local approach to effectively detect partial occlusion in the input face image. A face image is first divided into a finite number of disjointed local patch
56#
發(fā)表于 2025-3-31 07:50:52 | 只看該作者
Two-Dimensional Fisher Discriminant Analysis and Its Application to Face Recognitionrices are huge. In order to effectively deal with this problem, a new technique for two-dimensional(2D) Fisher discriminant analysis is developed in this paper. In the proposed algorithm, the Fisher criterion function is directly constructed in terms of image matrices. Then we utilize the Fisher cri
57#
發(fā)表于 2025-3-31 09:36:24 | 只看該作者
58#
發(fā)表于 2025-3-31 16:29:49 | 只看該作者
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發(fā)表于 2025-3-31 20:38:47 | 只看該作者
Recognize Multi-people Interaction Activity by PCA-HMMswith parameters of reduced dimensionality. Most existing work is based on HMMs and DBNs, and focuses on the interactions between two objects. However, longer feature vectors of HMMs usually lead to covariance matrix singularity in parameter learning and activity recognition. Moreover, arbitrary stru
60#
發(fā)表于 2025-3-31 23:35:08 | 只看該作者
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