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- W2034841142 abstract "Registration of partially overlapping 3D point clouds of an object is the initial phase in the 3D modeling pipeline. The automatic coarse alignment of a pair of 3D images is usually performed by 3D feature matching. Robust estimators like RANSAC are employed for 3D transformation estimation from point correspondences obtained by feature matching, in the presence of outliers. The number of RANSAC iterations required depends directly on the number of correspondences and inliers. Many variants of RANSAC have been proposed for the computer vision tasks like stereo matching, structure and motion estimation, image retrieval etc. This paper presents a study on the potential of two widely stated RANSAC variants - PROSAC and LoSAC - for 3D registration. Further, a new algorithm -ProLoSAC - which combines the relative merits of the two is proposed. The proposed algorithm has been evaluated on different pairs of partially overlapping 3D views of three different 3D models. The results indicate that the proposed algorithm finds the best transformation in less iteration compared to the other algorithms." @default.
- W2034841142 created "2016-06-24" @default.
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- W2034841142 date "2014-12-14" @default.
- W2034841142 modified "2023-09-27" @default.
- W2034841142 title "ProLoSAC" @default.
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- W2034841142 doi "https://doi.org/10.1145/2683483.2683513" @default.
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