Face Recognition Based on Sparse Similarity Sequence

摘要：

　　Mining and exploring novel discriminating information to boost the performance of the face recognition system is one of the current endeavored directions for face recognition.This paper explores the similarity information of faces belonging to different individuals and proposes a face recognition method based on sparse similarity sequence.Firstly,the concept of similarity sequence is defined to extract the similarity information of faces belonging to different individuals.Next,discriminating information is selected from the similarity sequence through Lasso sparse method.Further,a discrimination criterion is proposed to optimize the sparse degree of the sparse similarity sequence.Finally,the face recognition method is realized based on the optimal sparse similarity sequence.The EER of the proposed method reaches 0.05%and 0.01%respectively on two public face databases-the FacePix database and the FaceMLA database,showing outstanding advantage on performance.

关键词： Face recognition Similarity sequence Lasso sparse

作者: Qing Zhang Yilong Yin Gongping Yang

作者单位: School of Computer Science and Technology,Shandong University,Jinan,250101,China

会议类型: 国内会议

会议名称: 2014全国理论计算机科学学术年会

会议地点: 济南

会议语种:英文

页码: 1-11

在线出版日期: 2014-10-16（万方平台首次上网日期，不代表论文的发表时间）