tailieunhanh - báo cáo hóa học:" Research Article Adapted Active Appearance Models"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Adapted Active Appearance Models | Hindawi Publishing Corporation EURASIP Journal on Image and Video Processing Volume 2009 Article ID 945717 14 pages doi 2009 945717 Research Article Adapted Active Appearance Models Renaud Seguier 1 Sylvain Le Gallon 2 Gaspard Breton 2 and Christophe Garcia2 1SUPliLEC IETR Avenue de la Boulaie 35511 Cesson-Sevigne France 2 Orange Labs TECH IRIS 4 rue du clos courtel 35 512 Cesson Sevigne France Correspondence should be addressed to Renaud Seguier Received 5 January 2009 Revised 2 September 2009 Accepted 20 October 2009 Recommended by Kenneth M. Lam Active Appearance Models AAMs are able to align efficiently known faces under duress when face pose and illumination are controlled. We propose Adapted Active Appearance Models to align unknown faces in unknown poses and illuminations. Our proposal is based on the one hand on a specific transformation of the active model texture in an oriented map which changes the AAM normalization process on the other hand on the research made in a set of different precomputed models related to the most adapted AAM for an unknown face. Tests on public and private databases show the interest of our approach. It becomes possible to align unknown faces in real-time situations in which light and pose are not controlled. Copyright 2009 Renaud Seguier et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1. Introduction All applications related to face analysis and synthesis ManMachine Interaction compression in video communication augmented reality need to detect and then to align the user s face. This latest process consists in the precise localization of the eyes nose and mouth gravity center. Face detection can now be realized in real time and in a rather efficient manner 1 2 the technical bottleneck lies now in the face alignment when it is .