• CN:11-2187/TH
  • ISSN:0577-6686

›› 2006, Vol. 42 ›› Issue (7): 186-191.

• 论文 • 上一篇    下一篇

基于支持矢量机的从明暗恢复形状方法

尹爱军;秦树人;周传德   

  1. 重庆大学机械工程学院
  • 发布日期:2006-07-15

METHOD ON SHAPE FROM SHADING BASED ON SUPPORT VECTOR MACHINE

YIN Aijun;QIN Shuren;ZHOU Chuande   

  1. School of Mechanical Engineering, Chongqing University
  • Published:2006-07-15

摘要: 通过对传统从阴影到形状(Shape from shading, SFS)问题和支持矢量机(Supporting vector machine, SVM)的研究,提出一种基于SVM由从明暗恢复形状方法,详细分析了这一方法的理论依据和可行性,探讨了SVM输入参数的确定、核函数的选择与构造等关键问题。试验表明,与传统SFS方法相比,提出的方法能较准确地直接获取物体的高度值,且受环境因素影响小,无需作过多的成像条件假设。最后探讨了这一方法的改进方向。

关键词: SFS, SVM, 核函数, 深度预测

Abstract: By researching into the shape from shading(SFS) problem and supporting vector machine(SVM), a shape recovery method from light and shade based on SVM is proposed. The theoretical basis and feasibility of this method are analyzed, and key problems such as the determination of SVM input parameters and the choosing and constructing of core function are discussed. Examples show that compared to traditional SFS method, the method can acquire directly the height of an object relatively accurately, is affected by the environment slightly and need very few imaging condition assumption. At last, the direction to improve the method is discussed.

Key words: Depth forecast, Shape from shading, Supporting vector machine Kernel function

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