Multi-Modal Face Recognition

摘要：

In this paper, we exploit the multi-modal face recognition capability by a comparative study on 8 fusion methods in the score level, including Sum, Product, Max, Min, Decision Template (DT), DempsterShafer Rule (DS), Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) methods. Our experiments are based on the CASIA 3D Face Database and can be divided into two modes: verification and classification. Major conclusions are: (1) 2D modality can achieves similar performance as to 3D modality, and fusion scheme can substantially improve the recognition performance;(2) Product rule gives the best recognition performance in the simple fusion methods without training stage;(3) There is no guarantee that the complicated fusion methods with training stage will achieve better recognition performance than the simple fusion methods, and it is important to select the most suitable model for fusion according to the tasks.

作者: Haihong Shen Liqun Ma Qishan Zhang

作者单位: School of Electronic and Information Engineering Beijing University of Aeronautics and Astronautics School of Electronic and Information Engineering Beijing University of Aeronautics and Astronautics School of Electronic and Information Engineering Beijing University of Aeronautics and Astronautics

会议类型: 国际会议

会议名称: The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)

会议地点: 沈阳

会议语种:英文

页码: 612-616

在线出版日期: 2010-03-27（万方平台首次上网日期，不代表论文的发表时间）