农业机械学报2012，Vol.43Issue(2)：216-220,5.DOI:10.6041/j.issn.1000-1298.2012.02.041
基于支持向量回归的灰度图像三维形状重构
Shape from Shading Based on Support Vector Regression Algorithm
摘要
Abstract
In order to realize the shape from shading ( SFS) under unknown light source parameters of single grayscale image, an efficient SFS method was proposed based on support vector regression ( SVR) and particle swarm optimization( PSO) algorithm. Based on the SVR theory, a nonlinear mapping model was constructed between the grayscale image and its 3-D surface by researching into the SFS problem. The light source of the tested actual image should be estimated to generate the training samples corresponding to the light direction. It was important to select the proper SVR parameters for improvement on 3-D reconstruction precision, and the PSO algorithm was introduced. Finally, the case study had verified the feasibility and effectiveness of the proposed SFS method.关键词
灰度重构形状/未知光源/支持向量回归/粒子群优化算法Key words
Shape from shading/ Unknown light source/ Support vector regression/ Particle swarm optimization分类
信息技术与安全科学引用本文复制引用
胡志勇,张秀芬,徐敬华..基于支持向量回归的灰度图像三维形状重构[J].农业机械学报,2012,43(2):216-220,5.基金项目
国家青年科学基金资助项目(51005204)和内蒙古工业大学科学研究重点资助项目(ZD201110) （51005204）
