基于贝叶斯模型的快速立体匹配算法

摘要

To solve the fast stereo matching problem,a Bayesian probability model was proposed.Firstly,two-dimensional triangular meshes were generated from a set of robust sparse feature matching points.Then,the priori distribution function of disparity value based on triangular plane was established to reduce the ambiguity in the matching process.The algorithm can effectively use of disparity search space,and determine the disparity range automatically.It can be executed in parallel and gene-rate accurate dense disparity map without global optimization.Experimental results show that the algorithm can generate high accuracy dense disparity map for different scene images.For Cones image at 900×750 resolution,the running time of the algo-rithm is 0·3228 s.%为解决快速立体匹配问题，提出一种贝叶斯概率模型。依据鲁棒性稀疏特征匹配点集生成二维三角网格，基于三角形平面建立关于视差值的先验分布函数，减小剩余像素点匹配过程中的歧义性。该算法具有有效利用视差搜索空间、自动确定视差范围和可并行执行等优点，无需全局优化即可生成精确稠密的视差图。实验结果表明，对不同场景图像，该算法皆可生成高精度稠密视差图；对分辨率为900×750的 Cones 图像，该算法的运行时间为0·3228 s。