Integration of Gait and Side Face for Human Recognition in Video

摘要：

Combined with Two-Direction Image Matrix based Principal Component Analysis (2DIMPCA) and Multiple Discriminant Analysis (MDA), a new approach for human recognition is presented based on integrating information from gait and side face at the feature level. Feature exaction and dimension reducing is done to Gait Energy Image (GEI) and Side Face Image (SFI) respectively by 2DIMPCA, and two original feature vectors are obtained correspondingly, which are integrated into synthetic feature vectors. Then MDA is employed on the synthetic feature vectors of gait and side face to obtain fusion features vectors. Finally, the recognition process is implemented on the fusion feature vectors by nearest neighbor (NN) algorithm. The experimental results on Dataset B of CASIA gait databases show that: 1) the recognition rate of the integration of gait and side face is higher than that of the single feature of gait or side face; 2) the recognition rate of the proposed approach is slightly higher and the recognition time (not including the preprocessing time) is much shorter than that of the method in Ref. 7.

关键词： 2DIMPCA MDA Feature Fusion Gait Recognition Face Recognition

作者: Li Qi-Shen Lu Zhi-Tian Zhang Dan-Dan

作者单位: School of Computing Nanchang Hangkong University Nanchang, China

会议类型: 国际会议

会议名称: Second International Symposium on Electronic Commerce and Security(第二届电子商务与安全国际研究大会)(ISECS 2009)

会议地点: 南昌

会议语种:英文

页码: 721-725

在线出版日期: 2009-05-22（万方平台首次上网日期，不代表论文的发表时间）