%0 Journal Article
%T 采用彩色分割立体匹配与简化点云的三维目标快速重建<br>Fast Reconstruction of 3-D Object Based on Color Image Segmentation Stereo Matching and Point Cloud Reduction
%A 李鹤喜
%A 张娟娟
%A 孙玲云
%J Artificial Intelligence and Robotics Research
%P 55-61
%@ 2326-3423
%D 2014
%I Hans Publishing
%R 10.12677/AIRR.2014.34009
%X <div style=\"text-align:justify;\">
	<span style=\"line-height:1.5;\">本文将彩色分割立体匹配和简化点云技术用于三维目标的快速重建。对于采集的左右两幅三维目标图像，首先采用均值漂移算法进行彩色图像分割，然后按区域匹配算法进行快速立体匹配，获得初始视差，再应用置信传播法进行全局视差优化，从而得到精确的视差图与空间点云。应用空间表面曲率准则对获取的密集点云进行简化，并采用Delaunay三角剖分算法进行三维重建。实验结果表明：采用彩色图像分割与置信传播相结合，能够改善立体匹配效率并保证了匹配质量；基于曲率的点云简化，既提高了三维重建速度也得到了满意的重建效果。&lt;br/&gt;Color image segmentation stereo matching and point cloud reduction method is used for fast re-construction of 3-dimensional (3-D) object in this paper. For two captured images of a 3-D object, color image segmentation is first carried out using mean shift algorithm and initial disparity is computed using fast region-based stereo matching, and then the accurate disparity and point cloud of the 3-D object are obtained using belief propagation method to optimize global disparity. The 3-D object is reconstructed using Delaunay triangulation algorithm and point cloud reduction processing based on a surface curvature criterion. The experimental results show that the combi-nation of color image segmentation with belief propagation method can improve stereo matching efficiency and ensure matching quality, and the point cloud reduction technique can rise 3D re-construction speed and obtain satisfactory 3-D reconstruction result.</span><span style=\"line-height:1.5;\"></span>
</div>
%K 均值漂移，图像分割，立体匹配，点云，三维重建<br>Mean Shift
%K Image Segmentation
%K Stereo Matching
%K Point Cloud
%K 3D Reconstruction
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=14412