NDLI: Automatic non-rigid registration of 3D dynamic data for facial expression synthesis and transfer

Content Provider	IEEE Xplore Digital Library
Author	Sen Wang Gu, X.D. Hong Qin
Copyright Year	2008
Description	Author affiliation: Dept. of Comput. Sci., Stony Brook Univ., Stony Brook, NY (Sen Wang; Gu, X.D.; Hong Qin)
Abstract	Automatic non-rigid registration of 3D time-varying data is fundamental in many vision and graphics applications such as facial expression analysis, synthesis, and recognition. Despite many research advances in recent years, it still remains to be technically challenging, especially for 3D dynamic, densely-sampled facial data with a large number of degrees of freedom (necessarily used to represent rich and subtle facial expressions). In this paper, we present a new method for automatic non-rigid registration of 3D dynamic facial data using least-squares conformal maps, and based on this registration method, we also develop a new framework of facial expression synthesis and transfer. Nowadays more and more 3D dynamic, densely-sampled data become prevalent with the advancement of novel 3D scanning techniques. To analyze and utilize such huge 3D data, an efficient non-rigid registration algorithm is needed to establish one-to-one inter frame correspondences. Towards this goal, a non-rigid registration algorithm of 3D dynamic facial data is developed by using least-squares conformal maps with additional feature correspondences detected by employing active appearance models (AAM). The proposed method with additional, interior feature constraints guarantees that the non-rigid data will be accurately registered. The least-squares conformal maps between two 3D surfaces are globally optimized with the least angle distortion and the resulting 2D maps are stable and one-to-one. Furthermore, by using this non-rigid registration method, we develop a new system of facial expression synthesis and transfer. Finally, we perform a series of experiments to evaluate our non-rigid registration method and demonstrate its efficacy and efficiency in the applications of facial expression synthesis and transfer.
Starting Page	1
Ending Page	8
File Size	2207842
Page Count	8
File Format	PDF
ISBN	9781424422425
ISSN	10636919
DOI	10.1109/CVPR.2008.4587791
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-23
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Face detection Facial animation Computer vision Graphics Humans Tracking Algorithm design and analysis Heuristic algorithms Active appearance model Deformable models
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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