Vehicle recognition and tracking based on simulated annealing chaotic particle swarm optimization-Gauss particle filter algorithm

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(SA-CPSO-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.

Visualization of oil spill at sea surface based on texture projection

In view of the merits and demerits of current oil spill visualization methods,the paper involves a study on a new type of visualization approach targeting oil spill at sea.To be specific,the visualization of sea oil spill is implemented with the adoption of texture projection method.The texture projection-induced jaggedly edge is displayed in the performance test results.Under the circumstance,Gauss smoothing filter is introduced to secure the smooth convergence of texture edge and thus bring forth satisfactory dynamic visualization effect.Already,this means has already been successfully applied to the Oil Spill Emergency 3D Drilling System,which evidenced the validity and reliability of the new method.