CICP: Cluster Iterative Closest Point for sparse–dense point cloud registration

M. Lamine Tazir; Tawsif Gokhool; Paul Checchin; Laurent Malaterre; Laurent Trassoudaine

doi:10.1016/j.robot.2018.07.003

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JOURNAL ARTICLE

CICP: Cluster Iterative Closest Point for sparse–dense point cloud registration

M. Lamine Tazir Tawsif Gokhool Paul Checchin Laurent Malaterre Laurent Trassoudaine

Year: 2018 Journal: Robotics and Autonomous Systems Vol: 108 Pages: 66-86 Publisher: Elsevier BV

DOI: 10.1016/j.robot.2018.07.003

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Keywords:

Point cloud Computer science Artificial intelligence Computer vision Object (grammar) Point (geometry) Block (permutation group theory) Iterative closest point Point set registration Matching (statistics) Set (abstract data type) Mathematics Geometry

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Topics

Robotics and Sensor-Based Localization

Physical Sciences → Engineering → Aerospace Engineering

Robotic Path Planning Algorithms

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

3D Surveying and Cultural Heritage

Physical Sciences → Earth and Planetary Sciences → Geology

CICP: Cluster Iterative Closest Point for sparse–dense point cloud registration

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