Behavior recognition method based on space-time characteristic difference and correlation of skeleton data

The invention discloses a behavior recognition method based on space-time characteristic difference and correlation of skeleton data, and relates to the field of computer vision. A behavior recognition module built by the method comprises a space graph convolution module and a time graph convolution module; the spatial graph convolution module comprises a time feature learning unit, a channel feature learning unit and a time channel context topology unit, and the time feature learning unit and the channel feature learning unit are used for independently learning feature difference and feature correlation between joints in a time frame dimension and a channel dimension respectively; according to the method, a time channel context topology unit is used for learning the correlation of features between joints which cooperatively complete actions and learning the feature difference of part of joints which change due to movement, the time channel context topology unit learns global context feature ...