DocumentCode :
3021899
Title :
Accurate Dynamic Sketching of Faces from Video
Author :
Xu, Zijian ; Luo, Jiebo
Author_Institution :
Univ. of California Los Angeles, Los Angeles
fYear :
2007
fDate :
17-22 June 2007
Firstpage :
1
Lastpage :
7
Abstract :
A sketch captures the most informative part of an object, in a much more concise and potentially robust representation (e.g., for face recognition or new capabilities of manipulating faces). We have previously developed a framework for generating face sketches from still images. A more interesting question is can we generate an animated sketch from video? We adopt the same hierarchical compositional graph model originally developed for still images for face representation, where each graph node corresponds to a multimodal model of a certain facial feature (e.g., close mouth, open mouth, and wide-open mouth). To enforce temporal-spatial consistency and improve tracking efficiency, we constrain the transition of a graph node to be only between immediate neighboring modes (e.g. from closed mouth to open mouth but not to wide-open mouth), as well as by its corresponding parts in the neighboring frames. To improve the matching accuracy, we model the local structure of a given mode as a shape-constrained Markov network (SCMN) of image patches. The preliminary results show accurate sketching results from video clips.
Keywords :
Markov processes; face recognition; graph theory; image representation; video signal processing; face dynamic sketching; face recognition; hierarchical compositional graph model; image patches; multimodal model; robust representation; shape-constrained Markov network; temporal-spatial consistency; Active appearance model; Active shape model; Dictionaries; Eyes; Face detection; Face recognition; Facial animation; Head; Mouth; Robustness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 2007. CVPR '07. IEEE Conference on
Conference_Location :
Minneapolis, MN
ISSN :
1063-6919
Print_ISBN :
1-4244-1179-3
Electronic_ISBN :
1063-6919
Type :
conf
DOI :
10.1109/CVPR.2007.383488
Filename :
4270486
Link To Document :
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