The invention discloses a video behavior identification method based on an Attention-LSTM network. The method includes transforming the input RGB image sequence through an optical flow image sequencegeneration module to obtain an optical flow image sequence; inputting the optical flow graph sequence and the original RGB graph sequence into a time domain attention frame taking module, and respectively selecting non-redundant key frames in the two graph sequences; inputting the key frame sequences of the two images into an AlexNet network feature extraction module, respectively extracting timesequence features and spatial features of the two frame images, and performing a feature weight increasing operation with strong action correlation on the feature image output by the last convolutional layer through a feature weight increasing module; and inputting the feature maps output by the two AlexNet network feature extraction modules into an LSTM network behavior identification module, respectively identifying the two pictures, and fusing the two identification results in proportion through a fusion module to obtain a final video behavior identification result. According to the invention, the function of identifying the behavior from the video can be realized, and the identification accuracy can be improved.