DocumentCode :
3135978
Title :
Face recognition and alignment using support vector machines
Author :
Lam, Antony ; Shelton, Christian R.
Author_Institution :
Univ. of California, Riverside, CA
fYear :
2008
fDate :
17-19 Sept. 2008
Firstpage :
1
Lastpage :
6
Abstract :
Face recognition in the presence of pose changes remains a largely unsolved problem. Severe pose changes, resulting in dramatically different appearances, is one of the main difficulties. We present a support vector machine (SVM) based system that learns the relations between corresponding local regions of the face in different poses as well as a simple SVM based system for automatic alignment of faces in differing poses. We then present experimental results from multiple random splits of the CMU PIE Database to verify the strength of our approach.
Keywords :
face recognition; pose estimation; support vector machines; CMU PIE database; SVM; automatic face alignment; face recognition; pose change; support vector machine; Application software; Computer security; Data security; Ellipsoids; Face recognition; Facial features; Head; Image databases; Search engines; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automatic Face & Gesture Recognition, 2008. FG '08. 8th IEEE International Conference on
Conference_Location :
Amsterdam
Print_ISBN :
978-1-4244-2153-4
Electronic_ISBN :
978-1-4244-2154-1
Type :
conf
DOI :
10.1109/AFGR.2008.4813418
Filename :
4813418
Link To Document :
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