Integrating Scaling Strategy and Central Guided Voting for 3D Point Cloud Object Tracking-Reference-Cited by-同舟云学术

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Integrating Scaling Strategy and Central Guided Voting for 3D Point Cloud Object Tracking

Published:2024-04 Issue:4 Volume:9 Page:3940-3947
ISSN:2377-3766
Container-title:IEEE Robotics and Automation Letters
language:
Short-container-title:IEEE Robot. Autom. Lett.

Author:

Fan Baojie¹^ORCID,Zhou Wuyang¹^ORCID,Yang Yushi²^ORCID,Tian Jiandong³^ORCID

Affiliation:

1. College of Automation and College, Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing, China

2. College of Electronic and Optical Engineering, College of Flexible Electronics (Future Technology), Nanjing University of Posts and Telecommunications, Nanjing, China

3. Shenyang Institute of Automation, Chinese Academy of Science, Beijing, China

Funder

National Natural Science Foundation of China

Guangxi Key Laboratory of Machine Vision and Intelligent Control

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7083369/10440130/10453945.pdf?arnumber=10453945

Reference31 articles.

1. Are we ready for autonomous driving? The KITTI vision benchmark suite

2. PointNet: Deep learning on point sets for 3D classification and segmentation;Qi,2017

3. Leveraging Shape Completion for 3D Siamese Tracking

4. P2B: Point-to-Box Network for 3D Object Tracking in Point Clouds

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