Minimal Solvers For 3d Scan Alignment With Pairs Of Intersecting Lines

2020 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR)(2020)

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摘要
We explore the possibility of using line intersection constraints for 3D scan registration. Typical 3D registration algorithms exploit point and plane correspondences, while line intersection constraints have not been used in the context of 3D scan registration before. Constraints from a match of pairs of intersecting lines in two 3D scans can be seen as two 3D line intersections, a plane correspondence, and a point correspondence. In this paper, we present minimal solvers that combine these different type of constraints: 1) three line intersections and one point match; 2) one line intersection and two point matches; 3) three line intersections and one plane match; 4) one line intersection and two plane matches; and 5) one line intersection, one point match, and one plane match. To use all the available solvers, we present a hybrid RANSAC loop. We propose a non-linear refinement technique using all the inliers obtained from the RANSAC. Vast experiments with simulated data and two real-data data-sets show that the use of these features and the combined solvers improve the accuracy. The code is available at https://github.com/3DVisionISR/3DMinRegLineIntersect.
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关键词
point match,plane match,minimal solvers,3D scan alignment,line intersection constraints,3D scan registration,3D registration algorithms,plane correspondence,3D line intersections,point correspondence,intersecting line pairs,one point match,one plane match,hybrid RANSAC loop,nonlinear refinement technique,simulated data
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