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Detection of dominant planar surfaces in disparity images based on random sampling

机译:基于随机采样的视差图像主平面检测

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In this paper, the applicability of RANSAC-approach to planar surface detection in disparity images obtained by stereo vision is investigated. This study is specially focused on application in indoor environments, where many of the dominant surfaces are uniformly colored, which poses additional difficulties to stereo vision. Several simple modifications to the basic RANSAC-algorithm are examined and improvements achieved by these modifications are evaluated. Two simple performance measures for evaluating the accuracy of planar surface detection are proposed. An experimental study is performed using images acquired by a stereo vision system mounted on a mobile robot moving in an indoor environment.
机译:本文研究了RANSAC方法在立体视觉视差图像中平面检测中的适用性。这项研究专门针对室内环境中的应用,在这些环境中,许多主要表面均被均匀着色,这给立体视觉带来了更多困难。研究了对基本RANSAC算法的几个简单修改,并评估了通过这些修改实现的改进。提出了两种简单的性能指标,用于评估平面检测的准确性。使用由安装在室内环境中移动机器人上的立体视觉系统获取的图像进行实验研究。

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