Title :
Facial expression analysis by using KPCA
Author :
Jin, Zhong ; Davoine, Franck ; Lou, Zhen
Author_Institution :
Dept. of Comput. Sci., Nanjing Univ. of Sci. & Technol., China
Abstract :
This paper discussed a problem of robustness of existing kernel principal component analysis (KPCA) and proposed a new approach to do facial expression analysis by using KPCA. Experimental results on CMU facial expression image database and Yale database are encouraging.
Keywords :
covariance matrices; emotion recognition; face recognition; principal component analysis; Yale database; covariance matrices; facial expression analysis; facial expression image database; kernel PCA; robustness; Computer science; Covariance matrix; Data mining; Humans; Image databases; Independent component analysis; Kernel; Principal component analysis; Robustness; Spatial databases;
Conference_Titel :
Robotics, Intelligent Systems and Signal Processing, 2003. Proceedings. 2003 IEEE International Conference on
Print_ISBN :
0-7803-7925-X
DOI :
10.1109/RISSP.2003.1285676
