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Dec 14, 2021

An Improved Cross-Camera Vehicle Tracking Method: Re-Identification Feature Matching of Confidence Based on Spatio-Temporal Information

Publication: CICTP 2021

ABSTRACT

Intelligent Vehicle Infrastructure Cooperative Systems is a key research topic in the field of Intelligent Transportation Systems; traffic object perception based on cameras is one of its foundations. Due to the development of computer vision, single-camera traffic object tracking has implemented some advanced methods, but it is still inadequate in identity matching, especially because of more similar appearance. This study uses the background of multi-cameras and the DeepSORT algorithm as the basic framework to propose a vehicle identity matching algorithm based on the re-identification features determined by spatio-temporal information. The proposed method has been tested on a benchmark dataset of traffic video, achieving great performance and verifying its validity. Finally, this paper further discusses the advantages and disadvantages of the cross-camera vehicle tracking algorithm based on joint target matching of vehicle features and spatio-temporal information, contributing to the direction of future improvement of the algorithm.

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Go to CICTP 2021
CICTP 2021
Pages: 430 - 439

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Published online: Dec 14, 2021

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1Dept. of Automation, Tsinghua Univ., Shanghai Cleartv Co., Ltd. Joint Research Center for Video-Based Scenario Fusion Technology, Beijing, China. Email: [email protected]
Liangru Xiang [email protected]
2Dept. of Automation, Tsinghua Univ., Beijing, China. Email: [email protected]
Jianming Hu [email protected]
3Dept. of Automation, Tsinghua Univ., Shanghai Cleartv Co., Ltd. Joint Research Center for Video-Based Scenario Fusion Technology, Beijing, China. Email: [email protected]
4Dept. of Automation, Tsinghua Univ., Shanghai Cleartv Co., Ltd. Joint Research Center for Video-Based Scenario Fusion Technology, Beijing, China. Email: [email protected]

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