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首页> 外文会议>2011 International Conference on Multimedia Technology >Feature point detection and matching of wide baseline image based on scale space theory and guided matching algorithm
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Feature point detection and matching of wide baseline image based on scale space theory and guided matching algorithm

机译：基于尺度空间理论和引导匹配算法的宽基线图像特征点检测与匹配

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Image correspondence is a key issue in computer vision. Although many matching techniques in short baseline have been developed, the wide baseline correspondence problem with large scale, rotation, illumination and affine transformations is still not tackled very well. The paper analyses the defect of the traditional method and proposes a new matching method which based on multi-scale Harris algorithm and two-way guided matching to achieve large number of accurate point correspondences between un-calibrated image sequences of the same scene for wide baseline. Experimental results show that the guided matching method can be used for severe scene variations and provide evidence of improved performance with respect to the SIFT distance and Harris matchers. It is also useful to the matching in short baseline, and the results of this method are better than that of the traditional method.
机译：图像对应是计算机视觉中的关键问题。尽管已经开发了许多在短基线上的匹配技术，但是对于大规模，旋转，照明和仿射变换的宽基线对应问题仍然没有很好地解决。本文分析了传统方法的缺陷，提出了一种基于多尺度哈里斯算法和双向导引匹配的新匹配方法，可以在宽基线范围内实现同一场景未校准图像序列之间的大量精确点对应。 。实验结果表明，导引匹配方法可用于严重的场景变化，并提供了改善的SIFT距离和Harris匹配器性能的证据。这对于在短基线中进行匹配也很有用，并且该方法的结果优于传统方法。

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