3D Registration of the Point Cloud Data Using Parameter Adaptive Super4PCS Algorithm in Medical Image Analysis-Reference-Cited by-同舟云学术

3D Registration of the Point Cloud Data Using Parameter Adaptive Super4PCS Algorithm in Medical Image Analysis

Published:2021-11-12 Issue: Volume: Page:
ISSN:
Container-title:2021 4th International Conference on Digital Medicine and Image Processing
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Author:

Su Shun¹,Song Guoli²,Zhao Yiwen²

Affiliation:

1. the State Key Laboratory of Robotics, Shenyang Institute of Automation,Chinese Academy of Sciences, China and School of Computer Science and Technology, University of Chinese Academy of Sciences, China

2. the State Key Laboratory of Robotics, Shenyang Institute of Automation,Chinese Academy of Sciences, China and the Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, China

Funder

the National Natural Science Foundation of China

the National Key R&D Program of China

Youth Innovation Promotion Association of the Chinese Academy of Sciences

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3506651.3506652

Reference11 articles.

1. Registration of point cloud data from a geometric optimization perspective

2. Automatic Surface-Matching Spatial Registration Method for Neuronavigation Using Globally Optimal Iterative Closest Point

3. Go-ICP: Solving 3D Registration Efficiently and Globally Optimally

4. An Automated Calibration Method of Ultrasonic Probe Based on Coherent Point Drift Algorithm

5. Fankhauser P , Bloesch M , Rodriguez D , Kinect v2 for mobile robot navigation: Evaluation and modeling [C]//Advanced Robotics (ICAR) , 2015 International Conference on. IEEE , 2015: 388-394. Fankhauser P, Bloesch M, Rodriguez D, Kinect v2 for mobile robot navigation: Evaluation and modeling [C]//Advanced Robotics (ICAR), 2015 International Conference on. IEEE, 2015: 388-394.