一种基于特征约束的立体匹配算法

A Feature-Constrained Stereo Matching Algorithm

立体匹配一直是计算机视觉领域的一个中心研究问题 .为了得到适用于基于图象绘制技术的视图合成高密度视差图 ,提出了基于边缘特征约束的立体匹配算法 .该方法首先利用基于特征技术来得到边缘特征点的准确视差图 ,然后在边缘特征点视差图的约束下 ,对非边缘特征点采用区域相关算法进行匹配 ,这样既缩小了匹配搜索空间 ,又保证了匹配的可靠性 .边缘特征点和非边缘特征点的匹配采用双向匹配技术又进一步保证了匹配的可靠性 .实验结果表明 ,该算法效果良好 。

In the situation of image synthesis for image based rendering(IBR), we need not only precise matching but also a dense disparity map. In order to meet the needs of this application, a feature constrained stereo matching algorithm is presented. It integrates feature based and area based process. First we obtain a sparse precise disparity map of edge points using feature based approaches, next we fill in the disparity data of featureless points by using area based algorithm under the constraint of the acquired disparity map. In this way, not only can we reduce the search for correspondences but also ensure the validity of matching. During the matching phase the two images play a symmetric role to ensure the validity of matching. At the same time, the technique of stereo matching with adaptive window based on the gray value information of nearby points is adopted in the area based process. The experimental results show this algorithm is effective and it is of great value to use.