TY - GEN
T1 - A target tracking system based on multi-camera information fusion
AU - Cao, Minxuan
AU - Sun, Zhihao
AU - Han, Geng
AU - Deng, Fang
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - In order to promote the development of the public security sky-eyes system and the Internet of things, our system completes the integrated multi-camera cooperative tracking of multi-targets. The system uses the self-calibration method to map the camera detection results to the global coordinates through perspective transformation. The system uses YOLO-X network for target recognition and classification; The improved SORT algorithm is used to track and improve the ID switch problem. At the same time, 3D-box method is used to regress the attitude angle information of the object, so as to judge the state of the object and correct the deviation. On the premise of ensuring stability, the system achieves a faster running speed. It uses an RTX3080 GPU to accelerate, the overall speed reaches 60Hz, the classification accuracy is close to 100%, and stable target tracking is achieved. The system algorithm fully considers the occlusion, the change of target feature state, the disappearance of the target, etc., and can still ensure good results.
AB - In order to promote the development of the public security sky-eyes system and the Internet of things, our system completes the integrated multi-camera cooperative tracking of multi-targets. The system uses the self-calibration method to map the camera detection results to the global coordinates through perspective transformation. The system uses YOLO-X network for target recognition and classification; The improved SORT algorithm is used to track and improve the ID switch problem. At the same time, 3D-box method is used to regress the attitude angle information of the object, so as to judge the state of the object and correct the deviation. On the premise of ensuring stability, the system achieves a faster running speed. It uses an RTX3080 GPU to accelerate, the overall speed reaches 60Hz, the classification accuracy is close to 100%, and stable target tracking is achieved. The system algorithm fully considers the occlusion, the change of target feature state, the disappearance of the target, etc., and can still ensure good results.
KW - Attitude angle regression
KW - Information fusion
KW - Multi-target tracking
UR - http://www.scopus.com/inward/record.url?scp=85151121619&partnerID=8YFLogxK
U2 - 10.1109/CAC57257.2022.10055175
DO - 10.1109/CAC57257.2022.10055175
M3 - Conference contribution
AN - SCOPUS:85151121619
T3 - Proceedings - 2022 Chinese Automation Congress, CAC 2022
SP - 4225
EP - 4229
BT - Proceedings - 2022 Chinese Automation Congress, CAC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 Chinese Automation Congress, CAC 2022
Y2 - 25 November 2022 through 27 November 2022
ER -