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Iterative relaxational stereo matching based on adaptive support between disparities

机译:基于视差之间的自适应支持的迭代松弛立体匹配

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摘要

An adaptive relaxation method for stereo matching using matching probability and compatibility coefficients between disparities is presented. Relaxation labeling is an iterative procedure which reduces local ambiguity and noise, and selects the best label among several possible choices using compatibility coefficient. Stereo matching can be considered as labeling problem which assigns unique matches to feature points in the image. The compatibility coefficient between disparity classes is determined From highly reliable matches in the initial matching result and quantitatively expressed. The matching results of neighbor pixels support the center pixel through compatibility coefficients and update its matching probability. As the true matching results are propagated, so false matches are corrected and have high probability values. The conventional matching algorithms permit a uniform support from different disparity regions and it causes the degradation phenomena on the discontinuities of object. The results of experiments show that the proposed adaptive supporting method reduces the degradations and obtains fast convergence. (C) 1998 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved. [References: 24]
机译:提出了一种利用视差之间的匹配概率和相容系数进行立体匹配的自适应松弛方法。松弛标记是一种迭代过程,可减少局部歧义性和噪声,并使用兼容性系数在几种可能的选择中选择最佳标记。立体匹配可以被认为是标记问题,它为图像中的特征点分配了唯一的匹配项。视差类别之间的兼容性系数由初始匹配结果中的高度可靠的匹配确定并定量表示。相邻像素的匹配结果通过兼容性系数支持中心像素,并更新其匹配概率。随着正确匹配结果的传播,错误匹配将得到纠正并具有较高的概率值。传统的匹配算法允许来自不同视差区域的统一支持,并且会导致物体间断的退化现象。实验结果表明,所提出的自适应支持方法减少了退化并获得了快速收敛。 (C)1998模式识别学会。由Elsevier Science Ltd.出版。保留所有权利。 [参考:24]

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