3D LiDAR Point Cloud Registration Based on IMU Preintegration in Coal Mine Roadways [PDF]
Sensors, 2023 Point cloud registration is the basis of real-time environment perception for robots using 3D LiDAR and is also the key to robust simultaneous localization and mapping (SLAM) for robots.
Lin Yang +5 more
doaj +2 more sources
Robust and Fast Point Cloud Registration for Robot Localization Based on DBSCAN Clustering and Adaptive Segmentation [PDF]
SensorsThis paper proposes a registration approach rooted in point cloud clustering and segmentation, named Clustering and Segmentation Normal Distribution Transform (CSNDT), with the aim of improving the scope and efficiency of point cloud registration ...
Haibin Liu, Yanglei Tang, Huanjie Wang
doaj +2 more sources
Geometric Transformer for Fast and Robust Point Cloud Registration [PDF]
Computer Vision and Pattern Recognition, 2022 We study the problem of extracting accurate correspondences for point cloud registration. Recent keypoint-free methods bypass the detection of repeatable keypoints which is difficult in low-overlap scenarios, showing great potential in registration. They
Zheng Qin +5 more
semanticscholar +1 more source
A method of point cloud data block registration with considering distance from point to surface [PDF]
Bulletin of the Polish Academy of Sciences: Technical Sciences, 2022 The number of scanner stations used to acquire point cloud data is limited, resulting in poor data registration. As a result, a cloud point block registration approach was proposed that took into account the distance between the point and the surface ...
Yinju Lu, Mingyi Duan, Shuguang Dai
doaj +1 more source
GeoTransformer: Fast and Robust Point Cloud Registration With Geometric Transformer [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 We study the problem of extracting accurate correspondences for point cloud registration. Recent keypoint-free methods have shown great potential through bypassing the detection of repeatable keypoints which is difficult to do especially in low-overlap ...
Zheng Qin +7 more
semanticscholar +1 more source
PointDSC: Robust Point Cloud Registration using Deep Spatial Consistency [PDF]
Computer Vision and Pattern Recognition, 2021 Removing outlier correspondences is one of the critical steps for successful feature-based point cloud registration. Despite the increasing popularity of introducing deep learning techniques in this field, spatial consistency, which is essentially ...
Xuyang Bai +7 more
semanticscholar +1 more source
SC2-PCR: A Second Order Spatial Compatibility for Efficient and Robust Point Cloud Registration [PDF]
Computer Vision and Pattern Recognition, 2022 In this paper, we present a second order spatial compat-ibility (SC2) measure based method for efficient and robust point cloud registration (PCR), called SC2-PCR 1.
Zhi Chen, Kun Sun, Fan Yang, Wenbing Tao
semanticscholar +1 more source
Linear-Based Incremental Co-Registration of MLS and Photogrammetric Point Clouds
Remote Sensing, 2021 Today, mobile laser scanning and oblique photogrammetry are two standard urban remote sensing acquisition methods, and the cross-source point-cloud data obtained using these methods have significant differences and complementarity.
Shiming Li +4 more
doaj +1 more source
TEASER: Fast and Certifiable Point Cloud Registration [PDF]
IEEE Transactions on robotics, 2020 We propose the first fast and certifiable algorithm for the registration of two sets of three-dimensional (3-D) points in the presence of large amounts of outlier correspondences.
Heng Yang, J. Shi, L. Carlone
semanticscholar +1 more source
Learning Multiview 3D Point Cloud Registration [PDF]
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020 CVPR2020 - Camera ...
Gojcic, Zan +4 more
openaire +3 more sources