DocumentCode :
3197276
Title :
Hybrid-Boost Learning for Multi-Pose Face Detection and Facial Expression Recognition
Author :
Chen, Hsiuao Ying ; Huang, Chung Lin ; Fu, Chih Ming
Author_Institution :
Nat. Tsing-Hua Univ., Hsin-Chu
fYear :
2007
fDate :
2-5 July 2007
Firstpage :
671
Lastpage :
674
Abstract :
This paper proposes a novel multi-class hybrid-boost learning algorithm for multi-pose face detection and facial expression recognition. This system detects human face in different sizes, various poses, partial-occlusion, and different expressions. The contribution of this paper is the hybrid boosting algorithm combining the Haar-like (local) features and Gabor-like (global) features. The experimental results show that our system has better performance than the others.
Keywords :
Haar transforms; emotion recognition; face recognition; feature extraction; pose estimation; Gabor-like features; Haar-like features; facial expression recognition; human face; multi-class hybrid-boost learning algorithm; multi-pose face detection; partial-occlusion; Boosting; Face detection; Face recognition; Frequency; Humans; Image edge detection; Informatics; Infrared detectors; Iterative algorithms; Lighting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia and Expo, 2007 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
1-4244-1016-9
Electronic_ISBN :
1-4244-1017-7
Type :
conf
DOI :
10.1109/ICME.2007.4284739
Filename :
4284739
Link To Document :
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