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A stereo matching algorithm based on SIFT feature and homography matrix

机译:基于SIFT特征和单应矩阵的立体匹配算法

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摘要

Aiming at the low speed of traditional scale-invariant feature transform (SIFT) matching algorithm, an improved matching algorithm is proposed in this paper. Firstly, feature points are detected and the speed of feature points matching is improved by adding epipolar constraint; then according to the matching feature points, the homography matrix is obtained by the least square method; finally, according to the homography matrix, the points in the left image can be mapped into the right image, and if the distance between the mapping point and the matching point in the right image is smaller than the threshold value, the pair of matching points is retained, otherwise discarded. Experimental results show that with the improved matching algorithm, the matching time is reduced by 73.3% and the matching points are entirely correct. In addition, the improved method is robust to rotation and translation.
机译:针对传统的尺度不变特征变换(SIFT)匹配算法的低速度问题,提出了一种改进的匹配算法。首先,通过增加对极约束,检测特征点,提高特征点匹配的速度。然后根据匹配的特征点,用最小二乘法求出单应性矩阵。最后,根据单应性矩阵,可以将左图像中的点映射为右图像,如果映射点与右图像中的匹配点之间的距离小于阈值,则该对匹配点保留,否则丢弃。实验结果表明,改进后的匹配算法使匹配时间减少了73.3%,匹配点完全正确。另外,改进的方法对于旋转和平移具有鲁棒性。

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