Facial Expression Recognition Based on the Daul-Tree Complex Wavelet Transform and Supervised Spectral Analysis

摘要：

A novel feature extraction method is proposed in this paper named DTCW-SA which is based on the dual-tree complex wavelet transform and supervised spectral analysis for facial expression recognition. Although holding the property of multiresolution entirely, compared with traditional wavelet and Gabor transform, the attractive characteristics of DT-CWT are better orientation selectivity, approximate shift-invariance and lower redundancy. Different with existing DT-CWT, we extend images to appropriate size by interpolation before transform instead of copying the values of last row or column when decomposition of each scale. Whats more, the method of supervised spectral analysis can dig nonlinear information hidden in the data. Experiments on JAFFE database and CK database illustrate the efficiency of DTCW-SA, and the highest average rate of six expressions reaches 97.8％ on CK database.

关键词： dual-tree complex wavelet transform feature extraction spectral analysis

作者: Yadong Li Qiuqi Ruan Gaoyun An Xiaoli Li

作者单位: Institute of Information Science, Beijing Jiaotong University, Beijing 100044, 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: 1301-1304

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）