DocumentCode
3199968
Title
Realistic Facial Animation Synthesis and Transfer Based on Flexible Expression Ratio Image
Author
Xie, Pith ; Chen, Yiqiang ; Liu, Junfa
Author_Institution
Chinese Acad. of Sci., Beijing
fYear
2007
fDate
2-5 July 2007
Firstpage
1207
Lastpage
1210
Abstract
Geometry-controlled image warping performs well in exhibiting shape variations but bad in exhibiting wrinkle such as fossette. Successfully applied in expression cloning, expression ratio image (ERI) provides a way to quantize transferable common wrinkle. However, the warping used in ERI makes it difficult to restrain alignment error, which however prevents further analysis such as PCA. In this paper, flexible expression ratio image (FERI) is defined and further compressed as eigen FERI with PCA to quantize compactly common wrinkle. Based on FERI, a geometry-mapped mechanism consisting of shape-varying mechanism and wrinkling mechanism is constructed to synthesize and transfer realistic facial animation. Given the geometric parameter facial animation parameter (FAP), the shape variation deriving from shape-varying mechanism and the wrinkle deriving from wrinkling mechanism combine to generate realistic facial animation. Having no need for any example photo gallery but only two frontal neutral photos respective captured from source face and target face, as demonstrated in the experiment, the geometry-mapped mechanism based on FERI can map FAP series to the synchronous realistic source animation and target animation.
Keywords
computer animation; data compression; face recognition; image coding; principal component analysis; expression cloning; flexible expression ratio image; geometric parameter facial animation parameter; geometry-controlled image warping; image compression; principal component analysis; realistic facial animation synthesis; shape-varying mechanism; transferable common wrinkle quantization; Application software; Cloning; Computer graphics; Computer industry; Facial animation; Financial advantage program; Image coding; Machine learning algorithms; Principal component analysis; Shape;
fLanguage
English
Publisher
ieee
Conference_Titel
Multimedia and Expo, 2007 IEEE International Conference on
Conference_Location
Beijing
Print_ISBN
1-4244-1016-9
Electronic_ISBN
1-4244-1017-7
Type
conf
DOI
10.1109/ICME.2007.4284873
Filename
4284873
Link To Document