DocumentCode
1268508
Title
3-D facial model estimation from single front-view facial image
Author
Kuo, Chung J. ; Huang, Ruey-Song ; Lin, Tsang-Gang
Author_Institution
Inst. of Commun. Eng., Nat. Chung Cheng Univ., Chiayi, Taiwan
Volume
12
Issue
3
fYear
2002
fDate
3/1/2002 12:00:00 AM
Firstpage
183
Lastpage
192
Abstract
A 3-D facial model can be accurately obtained from: (1) stereo facial images or (2) front- and side-view facial images. The stereo images can be obtained by two different cameras at the same time. On the other hand, capturing front- and side-view facial images requires precise location of the camera. Either may be unavailable in many practical applications. We modify several existing techniques to automatically locate the feature point position from the front-view facial image. Then several schemes (such as minimum mean square error, minimum mean absolute error, and maximum a posteriori) are used to estimate the "depth" information of the 3-D facial model parameters from the single front-view facial image according to the anthropometric and a priori information. With this scheme, a 3-D facial model can be estimated from single front-view facial image. According to the simulation results, the estimated facial model matches the exact 3-D facial model, and the synthesized and original side-view facial images appear similar
Keywords
data compression; feature extraction; image reconstruction; parameter estimation; stereo image processing; video coding; 3D facial model estimation; anthropometric information; automatic feature point position location; cameras; depth information estimation; facial model coding; front-view facial image; maximum a posteriori; minimum mean absolute error; minimum mean square error; reconstructed faces; stereo facial images; video coding; Bit rate; Cameras; Communication channels; Face; Humans; Image coding; Mean square error methods; Signal synthesis; Video sequences; Visual communication;
fLanguage
English
Journal_Title
Circuits and Systems for Video Technology, IEEE Transactions on
Publisher
ieee
ISSN
1051-8215
Type
jour
DOI
10.1109/76.993439
Filename
993439
Link To Document