Orthogonal Tensor Marginal Fisher Analysis with Application to Facial Expression Recognition
A new tensor dimensionality reduction algorithm, Orthogonal Tensor Marginal Fisher Analysis (OTMFA), is proposed in this paper, which finds a set of orthonormal transformation matrices based on Tensor Marginal Fisher Analysis (TMFA). The obtained orthonormal transformation matrices do not distort the metric of the original tensor space such that the manifold structure of the input tensors can be better preserved. The experimental results show the effectiveness of the proposed algorithm for facial expression recognition.
Dimension reduction Orthogonal Tensor Marginal Fisher Analysis Facial expression recognition
Shuai Liu Qiuqi Ruan
Institute of Information Science Beijing Jiaotong University Beijing, China
国际会议
2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)
北京
英文
1710-1713
2010-08-24（万方平台首次上网日期，不代表论文的发表时间）