哈尔滨工业大学学报（英文版）2009，Vol.16Issue(2)：223-226,4.
Novel similarity measures for face representation based on local binary pattern
Novel similarity measures for face representation based on local binary pattern
ZHU Shi-hu 1FENG Ju-fu1
作者信息
- 1. Key Laboratory of Machine Perception Peking University, MOE Department of Machine Intelligence, School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China
- 折叠
摘要
Abstract
The successful face recognition based on local binary pattern (LBP) relies on the effective extraction of LBP features and the inferring of similarity between the extracted features. In this paper, we focus on the latter and propose two novel similarity measures for the local matching methods and the holistic matching methods respectively. One is Earth Mover's Distance with Hamming and Lp ground distance (EMD-HammingLp),which is a cross-bin dissimilarity measure for LBP histograms. The other is IMage Hamming Distance (IMHD),which is a dissimilarity measure for the whole LBP images. Experiments on FERET database show that the proposed two similarity measures outperform the state-of-the-art Chi-square similarity measure for extraction of LBP features.关键词
similarity measurement/local binary pattern/Earth Mover's Distance/IMage Euclidean DistanceKey words
similarity measurement/local binary pattern/Earth Mover's Distance/IMage Euclidean Distance分类
信息技术与安全科学引用本文复制引用
ZHU Shi-hu,FENG Ju-fu..Novel similarity measures for face representation based on local binary pattern[J].哈尔滨工业大学学报（英文版）,2009,16(2):223-226,4.
