3D Facial Expression Recognition Based on Basic Geometric Features

摘要：

This paper describes a 3D facial expression recognition approach based on distance and angle features, which can be got from the localized facial feature points. The probabilistic Neutral Network (PNN) architecture is used to classify the facial expressions based on BU-3DFE database. This paper adds the facial feature vectors with the information of slopes and the angles as the feature vectors got from the facial feature points, not only the distance information mentioned in the previous work. Thus it receives a better performance with an average recognition rate of 90.2％.

作者: Xiaoli Li Qiuqi Ruan Yue Ming

作者单位: Institution of information Science, Beijing Jiaotong University,Beijing,China

会议类型: 国际会议

会议名称: 2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)

会议地点: 北京

会议语种:英文

页码: 1366-1369

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）