文章摘要
WANG Weifeng(王伟峰)*,YANG Bo*,LIU Hanfei*,QIN Xuebin**.[J].高技术通讯(英文),2023,29(2):113~121
Vehicle recognition and tracking based on simulated annealing chaotic particle swarm optimization Gauss particle filter algorithm
  
DOI:10. 3772/ j. issn. 1006-6748. 2023. 02. 001
中文关键词: 
英文关键词: vehicle recognition, target tracking, annealing chaotic particle swarm, Gauss particle filter (GPF) algorithm
基金项目:
Author NameAffiliation
WANG Weifeng(王伟峰)* (*School of Safety Science and Engineering,Xi’an University of Science and Technology,Xi’an 710054,P.R.China) (**School of Electrical and Control Engineering,Xi’an University of Science and Technology,Xi’an 710054,P.R.China) 
YANG Bo* (*School of Safety Science and Engineering,Xi’an University of Science and Technology,Xi’an 710054,P.R.China) (**School of Electrical and Control Engineering,Xi’an University of Science and Technology,Xi’an 710054,P.R.China) 
LIU Hanfei* (*School of Safety Science and Engineering,Xi’an University of Science and Technology,Xi’an 710054,P.R.China) (**School of Electrical and Control Engineering,Xi’an University of Science and Technology,Xi’an 710054,P.R.China) 
QIN Xuebin** (*School of Safety Science and Engineering,Xi’an University of Science and Technology,Xi’an 710054,P.R.China) (**School of Electrical and Control Engineering,Xi’an University of Science and Technology,Xi’an 710054,P.R.China) 
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中文摘要:
      
英文摘要:
      Target recognition and tracking is an important research filed in the surveillance industry. Traditional target recognition and tracking is to track moving objects, however, for the detected moving objects the specific content can not be determined. In this paper, a multi-target vehicle recognition and tracking algorithm based on YOLO v5 network architecture is proposed. The specific content of moving objects are identified by the network architecture, furthermore, the simulated annealing chaotic mechanism is embedded in particle swarm optimization-Gauss particle filter algorithm. The proposed simulated annealing chaotic particle swarm optimization-Gauss particle filter algorithm (SACPSO-GPF) is used to track moving objects. The experiment shows that the algorithm has a good tracking effect for the vehicle in the monitoring range. The root mean square error (RMSE), running time and accuracy of the proposed method are superior to traditional methods. The proposed algorithm has very good application value.
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