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In order to quickly obtain a small video of a car accident from a large section of car accident video, the local information of the vehicle collision in the car accident video is accurately identified, so that the relevant department is notified as soon as possible to take rescue measures to avoid the occurrence of a second accident and achieve rapid assistance. Rescue, put forward a combination of space-time car accident identification method. Through the extraction and description of the local feature points of the car accident video, and the detection of the temporal and spatial corners of the local features of the car accident video, the temporal and spatial features of the car accident video are extracted. After the feature extraction, 3DSIFT, STIP and 3DHOG features of the car accident video can be obtained. These three features are respectively combined by different combinations of tandem fusion. After merging, 5 tandem results can be obtained, and K-MEANS clustering of the tandem features is performed. And KNN recognition to realize the recognition of car accident video. The experimental results show that using the algorithm of spatial-temporal correlation to identify the car accident can accurately find the fragments of car accidents, which can improve the accuracy of car accident recognition. Compared with the recognition rate of 33% obtained by the traditional algorithm, the video traffic accident recognition algorithm based on spatio-temporal correlation can improve the recognition accuracy of the crash to 62%.