A NEURAL-LEARNING-ALGORITHM-BASED SHAPE FROM SHADING SYSTEM

摘要：

This paper introduces a shape from shading (SFS) system,which is based on a neural learning algorithm. The system takes a single image of an object with a CCD camera and then reconstructs the object surface with a neural-learning-based SFS algorithm. This SFS algorithm solves and optimizes the neural elements, named network weights, by minimizing the cost function that is composed of the intensity constraint and the integrability constraint. This neural-learning-based SFS algorithm can provide a promising effectiveness and accuracy.Moreover, the reconstructed surface of this system can be applied in the area of surface measurement and defect detection.

关键词： Shape from shading Neural learning algorithm Lambertian reflectance model 3D reconstruction CCDcamera

作者: YUE-FANG GAO FEI LUO JIAN-ZHONG CAO

作者单位: College of Automation, South China University of Technology, Guangzhou 510640, China

会议类型: 国际会议

会议名称: 2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

会议地点: 大连

会议语种:英文

页码: 3991-3995

在线出版日期: 2006-08-13（万方平台首次上网日期，不代表论文的发表时间）