DocumentCode :
1660843
Title :
Multi-Component/Multi-Model AAM framework for face image modeling
Author :
Khan, Muhammad Asad ; Xydeas, Costas ; Ahmed, Hameeza
Author_Institution :
Infolab21, Lancaster Univ., Lancaster, UK
fYear :
2013
Firstpage :
2124
Lastpage :
2128
Abstract :
An image face modeling framework is proposed that aims to enhance the face modeling capability of the well known Active Appearance Model (AAM). AAM has been used successfully in person-specific related applications but it poses significant limitations when employed in generic face modeling. Thus this work is focused on the development of new face models which are generic in nature and which accurately fit unseen image faces, both in terms of shape and texture. For this purpose, images are decomposed into face related components which are subsequently clustered on the basis of shape similarities. Experimental results show that models generated through this novel framework can be significantly more effective than conventional AAM, in terms of both shape and texture.
Keywords :
face recognition; image texture; active appearance model; face image modeling; image shape; image texture; multicomponent-multimodel AAM framework; Abstracts; Active appearance model; Biomedical imaging; Computational modeling; Educational institutions; Active Appearance Models; Image Face Analysis and Synthesis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on
Conference_Location :
Vancouver, BC
ISSN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2013.6638029
Filename :
6638029
Link To Document :
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