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An efficient image matching method using Speed Up Robust Features

机译:一种高效的图像匹配方法,使用加速鲁棒功能

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The kernel of stereo vision system is stereo matching. In this paper proposed, an efficient image matching algorithm based on Speed Up Robust Features (SURF). Compared with traditional methods, this approach has enormous advantages of less computations and short time-consuming. The approach uses SURF algorithm to extract feature points. The feature descriptor of the approach is determined by Haar wavelet. The RANdom SAmple Consensus (RANSAC) algorithm is used to eliminate the false matches and wrong match point. The experimental results show that the approach is robust and has fast matching speed. That makes an important application field of 3D reconstruction.
机译:立体视觉系统的内核是立体声匹配。本文提出了一种基于加速鲁棒特征(冲浪)的有效图像匹配算法。与传统方法相比,这种方法具有较低的计算巨大优势和耗时短。该方法使用冲浪算法提取特征点。该方法的特征描述符由HAAR小波确定。随机样本共识(RANSAC)算法用于消除错误匹配和错误匹配点。实验结果表明,该方法是坚固的,匹配速度快。这使得3D重建的重要应用领域。

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