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ReigSAC: fast discrimination of spurious keypoint correspondences on planar surfaces

机译：ReigSAC：快速识别平面上的虚假关键点对应关系

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摘要

Various methods were proposed to detect/match special interest points (keypoints) in images and some of them (e.g., SIFT and SURF) are among the most cited techniques in computer vision research. This paper describes an algorithm to discriminate between genuine and spurious key-point correspondences on planar surfaces. We draw random samples of the set of correspondences, from which homogra-phies are obtained and their principal eigenvectors extracted. Density estimation on that feature space determines the most likely true transform. Such homography feeds a cost function that gives the goodness of each keypoint correspondence. Being similar to the well-known RANSAC strategy, the key finding is that the main eigenvector of the most (genuine) homographies tends to represent a similar direction. Hence, density estimation in the eigenspace dramatically reduces the number of transforms actually evaluated to obtain reliable estimations. Our experiments were performed on hard image data sets, and pointed that the proposed approach yields effectiveness similar to the RANSAC strategy, at significantly lower computational burden, in terms of the proportion between the number of homographies generated and those that are actually evaluated.
机译：提出了多种方法来检测/匹配图像中的特殊兴趣点（关键点），其中一些（例如SIFT和SURF）是计算机视觉研究中引用最多的技术之一。本文介绍了一种在平面上区分真实和伪造的关键点对应关系的算法。我们绘制对应关系集的随机样本，从中获取同构体并提取其主要特征向量。在该特征空间上的密度估计确定最可能的真实变换。这样的单应性提供了成本函数，该函数给出了每个关键点对应的优点。与众所周知的RANSAC策略相似，关键发现是大多数（正版）同形异义词的主要特征向量倾向于代表相似的方向。因此，本征空间中的密度估计会大大减少实际评估以获得可靠估计的转换次数。我们的实验是在硬图像数据集上进行的，并指出，所提出的方法在生成的单应字数量与实际评估的单字数量之间所占的比例非常低，产生的效率与RANSAC策略相似。

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  • 来源
    《Machine Vision and Applications》 |2014年第3期|763-773|共11页
  • 作者

    Hugo Proenca;

  • 作者单位

    Department of Computer Science, IT-Instituto de Telecomunicacoes, University of Beira Interior, 6200 Covilha, Portugal;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Keypoints detection; Keypoints matching; RANSAC;

    机译：关键点检测;关键点匹配;兰萨克;

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