IMPROVING RANSAC FEATURE MATCHING BASED ON GEOMETRIC RELATION
نویسندگان
چکیده
Abstract. Feature Matching between images is an essential task for many computer vision and photogrammetry applications, such as Structure from Motion (SFM), Surface Extraction, Visual Simultaneous Localization Mapping (VSLAM), vision-based localization navigation. Among the matched point pairs, there are typically false positive matches. Therefore, outlier detection rejection important steps in any application. RANSAC has been a well-established approach detection. The ratio number of required correspondences used determine iterations needed, which ultimately, determines computation time. We propose simple algorithm (GR_RANSAC) based on two-dimensional spatial relationships points image domain. assumption that distances bearing angles 2D feature should be similar with small disparity, case video sequences. In proposed approach, measured reference first its correspondence other image, significant differences considered outliers. This process can pre-filter points, thus increase inliers’ ratio. As result, GR_RANSAC converge to correct hypothesis fewer trial runs than ordinary RANSAC.
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ژورنال
عنوان ژورنال: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
سال: 2021
ISSN: ['1682-1777', '1682-1750', '2194-9034']
DOI: https://doi.org/10.5194/isprs-archives-xliii-b2-2021-321-2021