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GUIDED SPARSE FEATURE MATCHING VIA COARSELY DEFINED DENSE MATCHES

机译:通过粗定义的密实匹配进行引导的稀疏特征匹配

摘要

An example method is described herein. The method includes executing dense feature matching on an image pair that is down sampled to obtain a first set of feature correspondences for each pixel of the down sampled image pair. The method also includes calculating a neighborhood correspondence based on the first set of feature correspondences for each pixel in a first image of the image pair. Further, the method includes executing sparse feature matching on stereoscopic patch pairs from the image pair based on the neighborhood correspondence for each pixel to obtain correspondence estimates for each stereoscopic patch pair. Finally, the method includes refining the correspondence estimates for each stereoscopic patch pair to obtain a semi-dense set of feature correspondences by applying a geometric constraint to the correspondence estimates and retaining correspondences that satisfy the geometric constraint.
机译:本文描述了示例方法。该方法包括对向下采样的图像对执行密集特征匹配,以获得针对向下采样的图像对的每个像素的第一组特征对应关系。该方法还包括基于图像对的第一图像中的每个像素的第一组特征对应关系来计算邻域对应关系。此外,该方法包括基于每个像素的邻域对应关系对来自图像对的立体补丁对执行稀疏特征匹配,以获得每个立体补丁对的对应估计。最终,该方法包括通过将几何约束应用于对应估计并保留满足几何约束的对应,来细化针对每个立体补丁对的对应估计,以获得特征对应的半密集集合。

著录项

  • 公开/公告号US2019318196A1

    专利类型

  • 公开/公告日2019-10-17

    原文格式PDF

  • 申请/专利权人 INTEL CORPORATION;

    申请/专利号US201916455980

  • 发明设计人 OSCAR NESTARES;NILOUFAR POURIAN;

    申请日2019-06-28

  • 分类号G06K9/62;G06K9/46;

  • 国家 US

  • 入库时间 2022-08-21 12:12:38

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