In view of various situations caused by traffic jam, video analysis is used to realize real-time and efficient detection of vehicle queue length, so as to obtain more traffic information and improve traffic conditions. In this study, the improved FAST algorithm is obtained by combining the traditional FAST corner detection method with the process of motion detection. By using the improved FAST corner feature analysis technology, not only can the corner feature graph representing the presence of vehicles on the current traffic road be extracted, but also can the motion state of corner position be obtained. After the pretreatment of video under traffic monitoring, the static corner point features in a single lane form vehicle queuing, and PCA processing is carried out to obtain one-dimensional vector. Finally, morphological processing is carried out to detect the queue length of vehicles in a single lane. The experimental results show that the detection accuracy of this method is 98% on average, which can be applied to the actual scene.