A behavior recognition method based on a conversion module, relating to the field of human action recognition. The behavior recognition method based on a conversion module comprises: firstly, reading consecutive frames of images and constructing a mask; then constructing conversion module input data, which comprises acquiring the conversion module input data, and an operation regarding a position mask matrix (mask); performing action recognition by using a conversion module, which comprises a data pre-processing operation, and after data processing by a continuous coding module, obtaining an action detection result; and finally, calculating a cross-entropy loss for a category detection result with respect to a category label target, and optimizing network parameters. In the method, a conversion module used in natural language understanding is used for extracting spatio-temporal features of consecutive frames of images, and also, only the conversion module is used during the entire recognition process, such that the quantity of parameters in the method is reduced, the overall computation amount is reduced, and the action recognition frequency is improved.
BEHAVIOR RECOGNITION METHOD BASED ON CONVERSION MODULE