In order to address the issue of detection for weak and small moving targets in dynamic background,a classification method was proposed based on fast-LOF and optical flow trajectory.Weak and small moving objects only occupy a few pixels and are lack of features.To solve the problem,an idea of optical flow trajectory was introduced,and the abnormal optical flow trajectories were detected in high-dimensional space,so as to realize the detection of weak and small moving targets in dynamic background.To solve the problem of high complexity of the traditional LOF algorithm,fast-LOF was introduced to reduce the complexity of the anomaly detection link and ensure a good detection efficiency of the system.Experiments were carried out using videos captured by handheld cameras.The results showed that the algorithm can achieve rapid detection of weak and small moving targets with complex large field-of-view in white-light scenes.The combination of optical flow trajectory with fast-LOF effectively improved the performance and detection efficiency of the algorithm,which has certain value in visual detection systems.