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 ...

• Type: Conference
• Year: 2005
• Where: AVBPA
• Authors: Wenchao Zhang, Shiguang Shan, Hongming Zhang, Wen Gao, Xilin Chen
• Keywords: AVBPA 2005, Face Image, Feature Histogram, Histogram, Multimedia