基于分割树的移动机器人立体匹配研究.

This paper proposed a novel stereo matching method of the mobile robot based on segment tree to improve the speed and accuracy of depth recovery at the low texture, repeated texture and reflective environment. Firstly, it preprocessed the images for the mobile robot environment to reduce the influence of the light changes. In addition, this paper used the minimum spanning tree to weight the image pixels,and segmented the image by the segment tree. Then,it restored the depth of the occlusion area and the edge area that did not provide depth, and improved the accuracy of depth recovery. Finally, it carried out the comparison experiments. In indoor scenes, the calculation speed of this paper method was 187.140% faster than the ST-2 method, and semantic information could be provided for the mobile robot. On the Middlebury datasets, the calculation speed of this method was 157.500% faster than the ST-2 method, while the matching accuracy was improved 66. 547%. [ABSTRACT FROM AUTHOR]