Research on Object Detection Technology for Complex Motion Scenes
Aiming at the problems existing in moving object detection in complex traffic scenes,based on the Yolov5 model,this paper proposed a secondary optimization to improve cluster Anchor Boxes and introduced SE module algorithm to improve the iteration speed of clustering algorithms.Retinex image enhancement algorithm was used to improve the quality of image or video frames,so as to improve the precision and accuracy of the moving target recognition in the night or fog,haze,and other bad weather.Experimental results show that the proposed improved Yolov5 model can improve the average detection accuracy of moving target detection to a certain extent.Compared with the original Yolov5 model,the accuracy and recall rate of the improved algorithm are improved by 5.8%and 2.3%respectively.
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