Dynamic expression recognition method and system based on attention mechanism between space-time streams

The invention discloses a dynamic expression recognition method and system based on an attention mechanism between space-time streams. The method comprises the steps of firstly collecting facial expression video clips, and establishing a facial expression video library containing expression category labels; then constructing a double-flow convolutional neural network model embedded with an attention mechanism module between space-time flows, wherein the model comprises a data processing layer, a space flow branch, a time flow branch, the attention mechanism module between the space-time flows, a feature fusion layer, a full connection layer and a classification layer; training the model by using video samples in a facial expression video library; and finally, performing facial expression recognition on a newly input video by using the trained model. According to the method, the attention mechanism module between the space-time streams is embedded in the double-stream convolutional neural network, so that the