Gender Recognition Based on Multi-model Information Fusion

摘要：

In the paper, we proposed a gender recognition scheme based on multi-model information fusion. The proposed gender recognition scheme is composed of four parts: face detection and rectification, eye detection, feature extraction, and gender classifier. To evaluate the proposed scheme, a large number of images containing different-size faces are captured by using low-cost webcam. Experimental results show that our proposed scheme can detect facial regions as well as eyes well. In addition, the accuracy of our gender recognition scheme is more than 95％. These results demonstrate that our proposed scheme can achieve not only face and eye detection but also gender recognition.

作者: Guo-Shiang Lin Min-Kuan Chang Yu-Jui Chang

作者单位: Dept. of Computer Science and Information Engineering, Da Yeh University, Chang-Hua Dept. of Electrical Engineering, National Chung Hsing University, Tai-Chung

会议类型: 国际会议

会议名称: 2011亚太信号与信息处理协会年度峰会(APSIPAASC 2011)

会议地点: 西安

会议语种:英文

页码: 1-4

在线出版日期: 2011-10-18（万方平台首次上网日期，不代表论文的发表时间）