3D Point Cloud Coarse Registration based on Convex Hull Refined by ICP and NDT

Attia, Mouna; Slama, Yosr; Peyrodie, Laurent; Cao, Hongmei; Haddad, Farah

doi:10.1109/m2vip.2018.8600843

Cited by 4 publications

(2 citation statements)

References 15 publications

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“…In particular, when cell size is small, it requires more computing quantity and memory, while if the call size is big, the resolution of cells is high so that it results in less accurate registration [193]. Nevertheless, due to the attractive contribution of the NDT algorithm, an NDT-based solution is still a good choice in a fine-to-coarse strategy at the coarse step [198,199,200].…”

Section: Normal Distributionmentioning

confidence: 99%

A Tutorial Review on Point Cloud Registrations: Principle, Classification, Comparison, and Technology Challenges

Wang

Zhang

2021

Mathematical Problems in Engineering

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A point cloud as a collection of points is poised to bring about a revolution in acquiring and generating three-dimensional (3D) surface information of an object in 3D reconstruction, industrial inspection, and robotic manipulation. In this revolution, the most challenging but imperative process is point could registration, i.e., obtaining a spatial transformation that aligns and matches two point clouds acquired in two different coordinates. In this survey paper, we present the overview and basic principles, give systematical classification and comparison of various methods, and address existing technical problems in point cloud registration. This review attempts to serve as a tutorial to academic researchers and engineers outside this field and to promote discussion of a unified vision of point cloud registration. The goal is to help readers quickly get into the problems of their interests related to point could registration and to provide them with insights and guidance in finding out appropriate strategies and solutions.

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Section: Normal Distributionmentioning

confidence: 99%

A Tutorial Review on Point Cloud Registrations: Principle, Classification, Comparison, and Technology Challenges

Wang

Zhang

2021

Mathematical Problems in Engineering

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“…Attia M uses a combination of NDT and ICP algorithms. The experimental results show that using the ICP algorithm to coarsely register the point cloud and then using the NDT algorithm for refinement is better than directly using the ICP algorithm for refinement [ 24 ]. Wang Qingshan et al verified the reliability and accuracy of the combination of NDT and ICP algorithms in the campus environment [ 25 ].…”

Section: Introductionmentioning

confidence: 99%

Research on Point Cloud Registering Method of Tunneling Roadway Based on 3D NDT-ICP Algorithm

Yang

Wang

Luo

et al. 2021

Sensors

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In order to meet the needs of intelligent perception of the driving environment, a point cloud registering method based on 3D NDT-ICP algorithm is proposed to improve the modeling accuracy of tunneling roadway environments. Firstly, Voxel Grid filtering method is used to preprocess the point cloud of tunneling roadways to maintain the overall structure of the point cloud and reduce the number of point clouds. After that, the 3D NDT algorithm is used to solve the coordinate transformation of the point cloud in the tunneling roadway and the cell resolution of the algorithm is optimized according to the environmental features of the tunneling roadway. Finally, a kd-tree is introduced into the ICP algorithm for point pair search, and the Gauss–Newton method is used to optimize the solution of nonlinear objective function of the algorithm to complete accurate registering of tunneling roadway point clouds. The experimental results show that the 3D NDT algorithm can meet the resolution requirement when the cell resolution is set to 0.5 m under the condition of processing the point cloud with the environmental features of tunneling roadways. At this time, the registering time is the shortest. Compared with the NDT algorithm, ICP algorithm and traditional 3D NDT-ICP algorithm, the registering speed of the 3D NDT-ICP algorithm proposed in this paper is obviously improved and the registering error is smaller.

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A Fast Feature Extraction-Based Method for Globally Accurate Registration of Multi-View Point Clouds

Li,

Ou,

Lin

et al. 2024

2024 IEEE International Conference on Industrial Technology (ICIT)

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3D Point Cloud Coarse Registration based on Convex Hull Refined by ICP and NDT

Cited by 4 publications

References 15 publications

A Tutorial Review on Point Cloud Registrations: Principle, Classification, Comparison, and Technology Challenges

A Tutorial Review on Point Cloud Registrations: Principle, Classification, Comparison, and Technology Challenges

Research on Point Cloud Registering Method of Tunneling Roadway Based on 3D NDT-ICP Algorithm

A Fast Feature Extraction-Based Method for Globally Accurate Registration of Multi-View Point Clouds

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