DocumentCode :
3248872
Title :
Learning a single active face shape model across views
Author :
Romdhani, Sami ; Psarrou, Alexandra ; Gong, Shaogang
Author_Institution :
Sch. of Comput. Sci., Westminster Univ., Harrow, UK
fYear :
1999
fDate :
1999
Firstpage :
31
Lastpage :
38
Abstract :
An algorithm is described for modelling and recovering the shape of a face varying from the left to the right profile views. The method is based on a multi-view nonlinear model that utilises 2D view-dependent context without explicit reference to 3D structures. The model can cope with large nonlinear shape variations and inconsistent facial feature landmarks between wide varying views. For nonlinear model transformation, we adopt Kernel PCA based on the concept of support vector machines
Keywords :
computer vision; face recognition; learning (artificial intelligence); principal component analysis; 2D view-dependent context; Kernel PCA; active face shape model; face shape recovery; facial feature landmarks; learning; multi-view nonlinear model; nonlinear model transformation; profile views; support vector machines; Active shape model; Computer science; Computer vision; Context modeling; Educational institutions; Humans; Image reconstruction; Kernel; Principal component analysis; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems, 1999. Proceedings. International Workshop on
Conference_Location :
Corfu
Print_ISBN :
0-7695-0378-0
Type :
conf
DOI :
10.1109/RATFG.1999.799220
Filename :
799220
Link To Document :
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