Title :
Comparison of PCA and ICA in Face Recognition
Author :
Luo, Bing ; Hao, Yu-Jie ; Zhang, Wei-Hua ; Liu, Zhi-Shen
Author_Institution :
Univ. of Electron. Sci. & Technol. of China, Chengdu
Abstract :
Over the last ten years, face recognition has become a specialized applications area within the larger field of computer vision. Principal component analysis (PCA) and independent component analysis (ICA) become common method for face recognition. This paper compares Principal component analysis (PCA) to independent component analysis (ICA) in face recognition. In this paper, we used PCA derived from "eigenfaces". ICA derived from a linear representation of nongaussian data. In the paper, it shows the different between PCA and ICA.
Keywords :
computer vision; face recognition; independent component analysis; principal component analysis; ICA; PCA; computer vision; face recognition; independent component analysis; linear representation; nongaussian data; principal component analysis; Application software; Chemical technology; Computer vision; Face recognition; Image databases; Independent component analysis; Pixel; Principal component analysis; Signal generators; Statistical analysis; Face recognition; ICA (independent component analysis); PCA (principle component analysis);
Conference_Titel :
Apperceiving Computing and Intelligence Analysis, 2008. ICACIA 2008. International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-3427-5
Electronic_ISBN :
978-1-4244-3426-8
DOI :
10.1109/ICACIA.2008.4770014
