DocumentCode
2003230
Title
A Hybrid-reflectance-modeled and Neural-network-based Shape from Shading Algorithm
Author
Gao, Yuefang ; Luo, Fei ; Cao, Jianzhong
Author_Institution
South China Univ. of Technol., Guangzhou
fYear
2007
fDate
May 30 2007-June 1 2007
Firstpage
1014
Lastpage
1017
Abstract
This paper introduces a shape from shading algorithm which adopts a hybrid reflectance model and neural networks. Different from traditional neural-network-based algorithms, this algorithm considers both of the diffuse and specular reflections; on the other hand, also different from traditional hybrid-reflectance-modeled algorithms, this algorithm can adjust the surface albedo and the combination ratio between the diffuse and specular components according to a training algorithm. With the hybrid reflectance model, the algorithm can deal with various kinds of surfaces; with the neural network, the consistency can be improved and the reconstruction time can be greatly reduced. Experimental results at the end of this paper also prove the superiorities.
Keywords
image reconstruction; learning (artificial intelligence); neural nets; 3D image object shape reconstruction; hybrid reflectance modeled algorithm; neural network training algorithm; shape from shading algorithm; Automatic control; Automation; Educational institutions; Image reconstruction; Neural networks; Reflection; Reflectivity; Shape control; Subscriptions; Surface reconstruction; diffuse reflection; hybrid reflectance model; neural network; shape from shading; specular reflection;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Automation, 2007. ICCA 2007. IEEE International Conference on
Conference_Location
Guangzhou
Print_ISBN
978-1-4244-0818-4
Electronic_ISBN
978-1-4244-0818-4
Type
conf
DOI
10.1109/ICCA.2007.4376509
Filename
4376509
Link To Document