DocumentCode :
1561564
Title :
A Simple High Accuracy Approach for Face Recognition
Author :
Chen, Liang ; Tokuda, Naoyuki
Author_Institution :
Univ. of Northern British Columbia, Prince George
fYear :
2007
Firstpage :
92
Lastpage :
98
Abstract :
The theory that electoral college is more stable than direct popular vote is applied in face recognition. By simply adopting most traditional PCA approach, the experiments in this paper show a remarkably higher recognition rate than any known algorithm is reached with electoral college strategy on known FERET datasets. It indicates that a significant breakthrough can be expected by embedding electoral college with more effective face recognition algorithms.
Keywords :
face recognition; principal component analysis; FERET dataset; PCA approach; electoral college; face recognition; Associative memory; Cognitive informatics; Computer science; Educational institutions; Face recognition; Pattern matching; Pattern recognition; Pollution; Principal component analysis; Voting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cognitive Informatics, 6th IEEE International Conference on
Conference_Location :
Lake Tahoo, CA
Print_ISBN :
9781-4244-1327-0
Electronic_ISBN :
978-1-4244-1328-7
Type :
conf
DOI :
10.1109/COGINF.2007.4341877
Filename :
4341877
Link To Document :
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