3D Object Detection and Tracking Based on Lidar-Camera Fusion and IMM-UKF Algorithm Towards Highway Driving-Reference-Cited by-同舟云学术

3D Object Detection and Tracking Based on Lidar-Camera Fusion and IMM-UKF Algorithm Towards Highway Driving

Published:2023-08 Issue:4 Volume:7 Page:1242-1252
ISSN:2471-285X
Container-title:IEEE Transactions on Emerging Topics in Computational Intelligence
language:
Short-container-title:IEEE Trans. Emerg. Top. Comput. Intell.

Author:

Nie Chang¹,Ju Zhiyang²^ORCID,Sun Zhifeng³,Zhang Hui⁴^ORCID

Affiliation:

1. Department of Automation, Key Laboratory of System Control and Information Processing of Ministry of Education, Shanghai Jiao Tong University, Shanghai, China

2. School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China

3. Electricity Facilities Guangri Guangzhou Co., Ltd, Gaungzhou, China

4. School of Transportation Science and Engineering, Beihang University, Beijing, China

Funder

Guangzhou Innovation Leading Team

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computational Mathematics,Control and Optimization,Computer Science Applications

Link

http://xplorestaging.ieee.org/ielx7/7433297/10190085/10092267.pdf?arnumber=10092267

Reference39 articles.

1. Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Review

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3. Early Lane Change Prediction for Automated Driving Systems Using Multi-Task Attention-Based Convolutional Neural Networks

4. Feature Pyramid Networks for Object Detection

5. PointNet++: Deep hierarchical feature learning on point sets in a metric space;qi;Proc Int Conf Adv Neural Inf Process Syst,0

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