Paper Info
Title
A Lighting Robust Fitting Approach of 3D Morphable Model Using Spherical Harmonic Illumination
Abstract
3D morph able model (3DMM) is a powerful tool to recover 3D shape and texture from a single facial image. Its foundation consists of three models (i.e. face, camera, and illumination) which can simulate the formulation process of facial images. In this paper, we adopt a new illumination model, the Sphere Harmonic Illumination Model (SHIM), to the 3DMM fitting process. The new illumination model takes more lighting factors into consideration than the Phong's model. Then, we use a new optimization algorithm to optimize the shape and texture parameters simultaneously under SHIM. Compared with the the existing methods that used SHIM to recover only texture, both the shape and texture recovered by our algorithm are improved. The experiments on he CMU-PIE database also show that, compared to other state-of-the-art methods based on the Phong's model, the proposed approach enhances the robustness of the fitting of 3DMM against lighting variations.
Year
DOI
Venue
2014
10.1109/ICPR.2014.366
ICPR
Keywords
Field
DocType
shape recognition,face recognition,3dmm fitting process,lighting,curve fitting,lighting variations,texture parameter optimization,facial image formulation process simulation,cmu-pie database,3d shape recovery,lighting robust fitting approach,solid modelling,phong model,shim,image texture,sphere harmonic illumination model,3d texture recovery,shape parameter optimization,3d morphable model
Computer vision,Pattern recognition,Computer science,Image-based lighting,Harmonic,Spherical harmonics,Robustness (computer science),Artificial intelligence,Optimization algorithm,Shim (computing)
Conference
ISSN
Citations 
PageRank 
1051-4651
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Mingyang Ma120.70
Xiyuan Hu210819.03
Yuquan Xu3164.95
S. Peng433240.36