Computer Science ›› 2018, Vol. 45 ›› Issue (6): 308-313.doi: 10.11896/j.issn.1002-137X.2018.06.054

Special Issue: Face Recognition

• Graphics, Image & Pattern Recognition • Previous Articles     Next Articles

Fast Face Recognition Algorithm Based on Local Fusion Feature and Hierarchical Incremental Tree

ZHONG Rui1,2, WU Huai-yu1, HE Yun1   

  1. School of Information Science and Engineering,Wuhan University of Science and Technology,Wuhan 430081,China1;
    School of Mathematics and Computer Science,Gannan Normal University,Ganzhou,Jiangxi 341000,China2
  • Received:2017-01-05 Online:2018-06-15 Published:2018-07-24

Abstract: The off-line training and the high dimension of facial features in face recognition lead to the difficulty of achieving real-time processing performance.To solve this problem,the local fusion features and the hierarchical incremental tree were applied to construct a fast face recognition algorithm.Firstly,the supervised descent method(SDM) is used to locate the facial feature points.The feature of multi block-center symmetric local binary patterns(MB-CSLBP) in the neighborhood of each facial feature point is extracted and fused in series,which constitutes the proposed facial feature of local fusion feature of MB-CSLBP(LFP-MB-CSLBP).Then the above facial feature is sent into hierarchical incremental tree(HI-tree).Because the hierarchical clustering algorithm is used in the HI-tree to achieve incremental learning,it can train the recognition model online.Finally,the recognition rate and consuming time of the proposed algorithm are tested on three face databases and real application of video-based face recognition.The experimental results show that the proposed algorithm has better real-time computation and accuracy compared with other current approaches.

Key words: Hierarchical incremental tree, Incremental learning, Local fusion feature of MB-CSLBP, MB-CSLBP feature

CLC Number: 

  • TP391.41
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