Multi-vehicle Speed Measurement Based on Monitoring Video Using Improved Multi-object Tracking Algorithm-Reference-Cited by-同舟云学术

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Multi-vehicle Speed Measurement Based on Monitoring Video Using Improved Multi-object Tracking Algorithm

Published:2023-07-27 Issue: Volume: Page:
ISSN:
Container-title:2023 8th International Conference on Image, Vision and Computing (ICIVC)
language:
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Author:

Gao Xinwen¹,Gan Zhiyuan¹,Shen Zhuo²,Teng Li³

Affiliation:

1. School of Mechanical Engineering and Automation, SHU-SUCG Research Center of Building Industrialization, Shanghai University,Shanghai,China

2. SILC Business School, SHU-SUCG Research Center of Building Industrialization, Shanghai University,Shanghai,China

3. Shanghai Urban Construction City Operation (Group) Co., Ltd.,Shanghai,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10269794/10269801/10269975.pdf?arnumber=10269975

Reference20 articles.

1. Simple online and realtime tracking

2. Improving Convolutional Networks With Self-Calibrated Convolutions

3. Bytetrack: Multi-object tracking by associating every detection box;zhang;Computer Vision-ECCV 2022 17th European Conference Tel Aviv Israel October 23-27 2022 Proceedings Part XXII,0

4. Towards Real-Time Multi-Object Tracking

5. Stereo Visual Tracking Within Structured Environments for Measuring Vehicle Speed

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