DocumentCode :
2627143
Title :
Facial features detection robust to pose, illumination and identity
Author :
Gourier, Nicolas ; Hall, Daniela ; Crowley, James L.
Author_Institution :
GRAVIR Laboratory, INRIA, Montbonnot
Volume :
1
fYear :
0
fDate :
0-0 0
Firstpage :
617
Abstract :
This paper addresses the problem of automatic detection of salient facial features. Face images are described using local normalized Gaussian receptive fields. Face features are learned using a clustering of the Gaussian derivative responses. We have found that a single cluster provides a robust detector for salient facial features robust to pose, illumination and identity. In this paper we describe how this cluster is learned and which facial features have found to be salient
Keywords :
Gaussian processes; face recognition; feature extraction; Gaussian derivative responses; automatic detection; facial features detection; normalized Gaussian receptive fields; Computer vision; Cybernetics; Face detection; Facial features; Humans; Laboratories; Lighting; Pixel; Robustness; Skin;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics, 2004 IEEE International Conference on
Conference_Location :
The Hague
ISSN :
1062-922X
Print_ISBN :
0-7803-8566-7
Type :
conf
DOI :
10.1109/ICSMC.2004.1398368
Filename :
1398368
Link To Document :
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