DocumentCode :
1781384
Title :
A Fast 3-D Face Reconstruction Method
Author :
Changming Meng ; Fan Zhou ; Ruomei Wang
Author_Institution :
Sch. of Inf. Sci. & Technol., Sun Yat-sen Univ., Guangzhou, China
fYear :
2014
fDate :
28-30 Nov. 2014
Firstpage :
146
Lastpage :
150
Abstract :
Plausible human face reconstruction is an active topic of virtual human research and has amounts of achievements. However, most of them require abundant image source and complex manual operations. In this paper, we propose a method for reconstructing 3D face models using only one frontal face image. Six neutral head models of male and female in three human races are used as the prototypes and one of them is selected to be deformed into the particular face every time. Feature points are extracted from frontal image automatically. Then we link the feature points extracted from the 2D image to the points on the 3D model, and deform the model according to the relative position of the feature points using the radial basis function (RBF) algorithm. In order to make the deformed model more realistic, we use face texture restoration and texture mapping technology. The experiments show that this method can quickly and automatically generate a personalized and realistic face model.
Keywords :
face recognition; feature extraction; image reconstruction; image restoration; image texture; radial basis function networks; solid modelling; 3D model; RBF algorithm; face texture restoration; fast 3D face reconstruction method; feature points extraction; frontal face image; neutral head models; plausible human face reconstruction; radial basis function algorithm; texture mapping technology; virtual human research; Computational modeling; Deformable models; Face; Feature extraction; Image reconstruction; Solid modeling; Three-dimensional displays;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Home (ICDH), 2014 5th International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-1-4799-4285-5
Type :
conf
DOI :
10.1109/ICDH.2014.36
Filename :
6996751
Link To Document :
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