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
fDate :
May 30 2007-June 1 2007
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;
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
DOI :
10.1109/ICCA.2007.4376509