YANG Bing1, WANG Xiao-hua1,2, YANG Xin3, HUANG Xiao-xi1
1. Institute of Cognitive and Intelligent Computing, Hangzhou Dianzi University, Hangzhou 310018, China; 2. China Jiliang University, Hangzhou 310018, China; 3. Computer Science and Technology College, Dalian University of Technology, Dalian 116023, China
In order to extract the local and global facial features for effective face recognition in complex environment, a face recognition method based on histograms of oriented gradients (HOG) pyramid model was. This method constructs the HOG pyramid of face image by multiscale analysis and HOG feature maps extraction. The feature maps in each layer of HOG pyramid are respectively separated into several non-overlapping blocks from which the HOG histograms are built and concatenated into an improved feature vector that can be used as the face descriptor later. Face recognition is performed throughout the similarity calculation among above feature vectors by using nearest neighbor classifier.Face recognition experimental results on the face recognition technology (FERET) database that captured under complicate changes of light and time environments demonstrate that the proposed method is of highly discriminable ability and good robustness in face recognition.
YANG Bing, WANG Xiao-hua, YANG Xin, HUANG Xiao-xi. Face recognition method based on HOG pyramid. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2014, 48(9): 1564-1569.
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