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Stereoscopic Face Reconstruction from a Single 2-Dimensional Face Image Using Orthogonality of Normal Surface and Y-Ratio.

Authors :
Srichumroenrattana, Natchamol
Lipikorn, Rajalida
Lursinsap, Chidchanok
Source :
International Journal of Pattern Recognition & Artificial Intelligence; Feb2016, Vol. 30 Issue 2, p-1, 27p
Publication Year :
2016

Abstract

This paper modified the method of three-dimensional (3-dimensional) face reconstruction from a single two-dimensional (2-dimensional) image based on the Lambertian model consisting of height estimation, normal surface estimation, albedo calculation and image normalization, normal surface calculation, actual height calculation, and error correction. In height estimation, the facial height of each input image is estimated from the average facial height of face images in the training data set. The estimated height is used for estimating the normal surface by applying our proposed pattern morphing method (PMM). To calculate the actual normal surface, the albedo of the input face image is calculated to normalize the image first. Then, the actual normal surface is derived by using our proposed Y-ratio calculation with improved computational time. Finally, the actual height of input face image is computed afterwards to construct the 3-dimensional face. Two face databases of 110 human face images containing 10 real and 100 synthetic images were tested by our proposed method with uniform reflectance and high level of heterogeneous reflectance abilities. The experimental results were compared with the results obtained from other existing methods, such as the traditional minimization, shape propagation, local, and linear approaches. Our method can accurately reconstruct 3-dimensional face from a single 2-dimensional face image with the error less than 6%. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02180014
Volume :
30
Issue :
2
Database :
Complementary Index
Journal :
International Journal of Pattern Recognition & Artificial Intelligence
Publication Type :
Academic Journal
Accession number :
113205540
Full Text :
https://doi.org/10.1142/S0218001416550065