Accurate and Efficient Moving Object Detection with Optical Flow
When using the classic HS optical flow method to recognize and detect moving targets in video images,there are problems such as high environmental noise and low detection efficiency.To this end,improvements were made to the optical flow method.Firstly,design a new judgment method to reduce the number of iterations for solving optical flow and the execution time of the algorithm;Then,combining edge de-tection and other algorithms,design algorithms that meet accuracy constraints to reduce the impact of environmental noise;Finally,GPU was used to optimize the optical flow method and edge detection algorithm in parallel,thereby further improving the efficiency of the algorithm.The experimental results show that the proposed algorithm has a detection accuracy of 88.1％on the CDNet2014 dataset,and the detected moving targets have high clarity.In addition,the maximum acceleration ratio of this algorithm on GPU is 89 times,which greatly improves its perfor-mance compared to traditional algorithms.
万方数据
维普
