Name
Abstract | ||
|---|---|---|
In this correspondence, we address the facial expression recognition problem using kernel canonical correlation analysis (KCCA). Following the method proposed by Lyons et al. and Zhang et al., we manually locate 34 landmark points from each facial image and then convert these geometric points into a labeled graph (LG) vector using the Gabor wavelet transformation method to represent the facial features. On the other hand, for each training facial image, the semantic ratings describing the basic expressions are combined into a six-dimensional semantic expression vector. Learning the correlation between the LG vector and the semantic expression vector is performed by KCCA. According to this correlation, we estimate the associated semantic expression vector of a given test image and then perform the expression classification according to this estimated semantic expression vector. Moreover, we also propose an improved KCCA algorithm to tackle the singularity problem of the Gram matrix. The experimental results on the Japanese female facial expression database and the Ekman's "Pictures of Facial Affect" database illustrate the effectiveness of the proposed method. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/TNN.2005.860849 | IEEE Transactions on Neural Networks |
Keywords | Field | DocType |
six-dimensional semantic expression vector,kernel canonical correlation analysis,associated semantic expression vector,facial expression recognition problem,estimated semantic expression vector,japanese female facial expression,basic expression,lg vector,facial feature,expression classification,semantic expression vector,face recognition,generalized discriminant analysis,kernel method,graph theory,facial expression,gabor wavelets,wavelet transforms | Expression (mathematics),Gabor wavelet,Computer science,Gabor filter,Artificial intelligence,Standard test image,Facial recognition system,Pattern recognition,Speech recognition,Facial expression,Linear discriminant analysis,Kernel method,Machine learning | Journal |
Volume | Issue | ISSN |
17 | 1 | 1045-9227 |
Citations | PageRank | References |
113 | 3.69 | 15 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wenming Zheng | 1 | 1240 | 80.70 |
| Xiaoyan Zhou | 2 | 144 | 7.80 |
| Cairong Zou | 3 | 415 | 27.19 |
| Li Zhao | 4 | 380 | 27.36 |