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Matching algorithm of binocular dynamic vision measurement

机译：双目动态视觉测量匹配算法

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摘要

In order to realize the correspondence of feature points in the binocular dynamic vision measurement system, the two homologous images matching problem in the paper is studied. First of all, a method of strong space resection. The strong space resection optimizes the elements of exterior orientation, improves the precision, so as to improve the calculating precision of epipolar line. Secondly, an algorithm of multiple restriction matching which is for two homologous images matching of feature points has been introduced. This algorithm based on epipolar line constrain, increases the uniqueness constraint and double constraint, combined with the second match with disparity gradient constrain, finally get the correct matching relationship of feature points in two homologous images. The experimental results show that: this method for matching of binocular dynamic vision measurement system, can get 100% of the matching accuracy rate. And it would satisfy the need of binocular dynamic vision measurement system.
机译：为了实现双目动态视觉测量系统中特征点的对应关系，研究了纸上的两个同源图像匹配问题。首先，一种强大的太空切除方法。强大的空间切除优化了外部方向的元素，提高了精度，从而提高了截二偏极线的计算精度。其次，已经介绍了一种用于两个具有特征点的同源图像匹配的多个限制匹配的算法。该算法基于末极线约束，增加了唯一约束和双约束，与差异梯度约束的第二匹配结合，最后得到两个同源图像中特征点的正确匹配关系。实验结果表明：这种用于双目动态视觉测量系统的匹配方法，可以获得100％的匹配精度率。它可以满足双目动态视觉测量系统的需求。

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