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An algorithm based on photo consistency for image feature point matching

机译:一种基于图像特征点匹配照片一致性的算法

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Matching image feature point by the SURF (Speed-up Robust Features) algorithm needs to loop through all feature points on the image to be matched, which will take a long computation time. In order to solve this problem, it is proved based on the photo consistency that the Hessian matrix determinants between the matched feature points are equal in theory. Experimental results show that because of the influences of light and other elements, the ratio of the Hessian matrix determinant of 95 percent of the correct SURF feature point's pairs is between 0.7 and 1.5. Based on the relation of the Hessian matrix determinants between the matched feature points, a fast image feature point matching algorithm is proposed, which improves the recognition rate of feature points, and it makes over twice faster than the SURF algorithm.
机译:匹配的图像特征点由冲浪(加速鲁棒功能)算法需要循环通过待匹配的图像上的所有功能点,这将需要长时间的计算时间。为了解决这个问题,基于匹配特征点之间的Hessian矩阵决定因素在理论上相等的照片一致性证明。实验结果表明,由于光和其他元素的影响,Hessian基质决定簇的95%的正确冲浪特征点对的比率在0.7和1.5之间。基于匹配特征点之间的Hessian矩阵确定剂的关系,提出了一种快速图像特征点匹配算法,其提高了特征点的识别率,并且它比冲浪算法快两倍。

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