3 results about "Action status" patented technology

An action state estimation apparatus is provided that includes a sampling portion, an action state model storage, and an estimation calculation portion. The sampling portion samples a displacement measurement signal within a predetermined time and generates displacement measurement data based on the sampled displacement measurement signal. The action state model storage stores an action state model modeled by associating the displacement measurement data with a loaded state of a muscle of the test subject. The estimation calculation portion then estimates the loaded state by setting the displacement measurement data as an input vector and using the action state model.

An action state estimation apparatus is provided that includes a sampling portion, a statistic calculation portion, an action state model storage, and an estimation calculation portion. The sampling portion samples a displacement measurement signal within a predetermined time and generates displacement measurement data. The statistic calculation portion calculates a statistic of the displacement measurement data. The action state model storage stores an action state model modeled by associating the statistic with a loaded state of a muscle of the test subject. The estimation calculation portion estimates the loaded state by setting the statistic as an input vector and using the action state model.

The application discloses a method for training an action generation model, an action generation method, an action generation device and an action generation equipment, and relates to machine learning of artificial intelligence. The method comprises the following steps: calling an action encoder to perform action feature extraction on an action state of a virtual character to obtain an action code; calling a style encoder to perform style feature extraction on the action state of the virtual character to obtain a style code; calling a decoder to decode the action code and the style code to obtain a predicted action of the virtual character; calculating a style loss according to the style codes of different action states; calculating an action loss according to the action codes of different action states; calculating a reconstruction loss according to a real action corresponding to an action state and the predicted action; and training the action generation model according to the action loss, the style loss and the reconstruction loss. The method can distinguish the action styles of different virtual characters and improve the action quality of the generated virtual characters.