Target-less registration of point clouds: A review

December 29, 2019 ยท The Cartographer ยท ๐Ÿ› arXiv.org

๐Ÿ“š THE CARTOGRAPHER: The Cartographer
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"Title-pattern auto-detect: Target-less registration of point clouds: A review"

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Authors Yue Pan arXiv ID 1912.12756 Category cs.CV: Computer Vision Cross-listed cs.RO Citations 1 Venue arXiv.org Last Checked 4 days ago
Abstract
Point cloud registration has been one of the basic steps of point cloud processing, which has a lot of applications in remote sensing and robotics. In this report, we summarized the basic workflow of target-less point cloud registration,namely correspondence determination and transformation estimation. Then we reviewed three commonly used groups of registration approaches, namely the feature matching based methods, the iterative closest points algorithm and the randomly hypothesis and verify based methods. Besides, we analyzed the advantage and disadvantage of these methods are introduced their common application scenarios. At last, we discussed the challenges of current point cloud registration methods and proposed several open questions for the future development of automatic registration approaches.
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