GENDER RECOGNITION BASED ON FUSION OF FACE AND GAIT INFORMATION

摘要：

This paper considers the combination of face and gait biometrics from the same walking sequence to carry out gender recognition. A camera is capturing the side view of a person, while another camera is placed to record the face of the same person at the front view. After these videos are acquired, we extract the silhouette images from the gait videos and normalized frame images decomposed from the face videos. Then, for face classification, we introduce PCA to reduce the image dimension and SVM to classify gender, for gait classification, we divide the silhouette into seven parts and extract features from each and also employ SVM to classify gender. On the decision level, the sum rule is applied to implement the fusion of these two classification results. The final fusion results show an improvement on correct classification rate.

关键词： Fusion Silhouette Face Gender recognition Sum rule

作者: DE ZHANG YUN-HONG WANG

作者单位: Intelligent Recognition and Image Processing Laboratory, School of Computer Science and Engineering, Beihang University, Beijing 100083, China

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 62-67

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）