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AVBPA
2005
Springer

Multi-resolution Histograms of Local Variation Patterns (MHLVP) for Robust Face Recognition

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Multi-resolution Histograms of Local Variation Patterns (MHLVP) for Robust Face Recognition
This paper presents a novel approach to face recognition, named Multi-resolution Histograms of Local Variation Patterns (MHLVP), in which face images are represented as the concatenation of the local spatial histogram of local variation patterns computed from the multi-resolution Gabor features. For a face image with abundant texture and shape information, a Gabor feature map(GFM) is computed by convolving the image with each of the forty multiscale and multi-orientation Gabor filters. Each GFM is then divided into small non-overlapping regions to enhance its shape information, and then Local Binary Pattern (LBP) histograms are extracted for each region and concatenated into a feature histogram to enhance the texture information in the specific GFM. Further more, all of the feature histograms extracted from the forty GFMs are further concatenated into a single feature histogram as the final representation of the given face image. Eventually, the identification is achieved by histogram ...
Wenchao Zhang, Shiguang Shan, Hongming Zhang, Wen
Added 26 Jun 2010
Updated 26 Jun 2010
Type Conference
Year 2005
Where AVBPA
Authors Wenchao Zhang, Shiguang Shan, Hongming Zhang, Wen Gao, Xilin Chen
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