Title :
Comparative study: face recognition on unspecific persons using linear subspace methods
Author :
Lin, Dahua ; Yan, Shuicheng ; Tang, Xiaoou
Author_Institution :
Dept. of Inf. Eng., Chinese Univ. of Hong Kong, Shatin, China
Abstract :
Recently many automatic face recognition (AFR) systems were developed for applications with unspecific persons, which is different from conventional pattern recognition problems where all classes are known in the training stage. In this paper, we present a systematic and comprehensive study on linear subspace methods for face recognition on unspecific persons. Over 6700 experiments using different algorithms with different training parameters and testing conditions are conducted on a large scale database (4550 samples) to investigate the compound effect of various influential factors. The observations based on these experiments are expected to provide widely applicable guidelines for designing practical AFR systems.
Keywords :
face recognition; principal component analysis; automatic face recognition systems; large scale database; linear subspace methods; pattern recognition problems; training parameters; unspecific persons; Face recognition; Guidelines; Large-scale systems; Linear discriminant analysis; Pattern recognition; Performance analysis; Principal component analysis; Scattering; Spatial databases; Testing;
Conference_Titel :
Image Processing, 2005. ICIP 2005. IEEE International Conference on
Print_ISBN :
0-7803-9134-9
DOI :
10.1109/ICIP.2005.1530504
