Research on Motion Target Detection Method Based on Machine Learning

In the development of modern science and technology, due to the small size, low cost, practical operation is very flexible, so the UAV has been fully used in environmental monitoring, geological survey, military exploration, agricultural plant protection and other fields. Among them, as one of the basic contents of UAV aerial photography research, moving target detection directly affects the quality and efficiency of UAV work. On the basis of understanding the research status of moving target detection methods, I choose random forest and kernel correlation filtering algorithms for experimental analysis, focusing on the application value of the algorithm in moving target detection. Finally, the experimental results show that the proposed algorithm is effective.