Gender Categorization Based On 3D Faces

摘要：

In this paper, we evaluate the gender classification performance based on 3D faces according to three aspects: image resolution, data fusion and texture descriptor. Our experiments are based on CASIA 3D Face Database, which has 123 individuals in total including different expressions. Main conclusions are as follows: (1) Image resolution has little influence on the gender categorization performance, and there is no guarantee that higher resolution images can obtain better results. (2) Fusion is useful to improve the categorization performance in each single modality. (3) Good local texture descriptors can substantially improve the gender categorization performance, which is even better than that in fusion.

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: 617-620

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）