计算机工程与应用2012，Vol.48Issue(7)：172-173,211,3.DOI:10.3778/j.issn.1002-8331.2012.07.045
稀疏判决分析在表情识别中的应用
Sparse discriminant analysis for expression recognition.
黄勇1
作者信息
- 1. 柳州铁道职业技术学院电子工程系,广西柳州545007
- 折叠
摘要
Abstract
A facial expression recognition method based on Sparse Discriminant Analysis(SDA) is proposed in this paper. The graph in SDA is constructed by sparse representation and incorporate Semi-Supervised Discriminant Analysis (SSDA), thus the local structure information is automatically modeled, and with the natural discriminative power of sparse representation, SDA can get better performance only resorting to few extra unlabeled samples. Experimental result on JAFFE and CED-WYU show that SDA is an effective method for improving the recognition accuracy.关键词
稀疏表述/线性判决分析/半监督判决分析/稀疏判决分析/表情识别Key words
sparse representation/Linear Discriminant Analysis(LDA)/Semi-Supervised Discriminant Analysis(SSDA)/Sparse Discriminant Analysis (SDA)/expression recognition分类
信息技术与安全科学引用本文复制引用
黄勇..稀疏判决分析在表情识别中的应用[J].计算机工程与应用,2012,48(7):172-173,211,3.
