Abstract: The present disclosure relates to methods and apparatuses for dynamic action detection and dynamic action control. A dynamic action detection method includes: adding an image frame in a video stream into a first queue, to obtain the first queue with a partially updated image frame; detecting a dynamic action in the partially updated image frame; and in response to the dynamic action not matching with the action detection result, updating an action detection result according to the dynamic action, the action detection result including an action reference result or a previously detected action detection result. A dynamic action detection in the present disclosure is executed according to the partially updated image frame in the first queue, so that the dynamic action can be detected more timely; and the dynamic action can also be rapidly determined, so that the action detection result is more accurate and the detection efficiency is higher.

Abstract: The present disclosure relates to dynamic action detection methods and apparatuses, and dynamic action control methods and apparatuses. The dynamic action detection method includes: adding an image frame in a video stream into a first queue, to obtain the first queue with a partially updated image frame; detecting a dynamic action in the partially updated image frame in the first queue; and updating an action detection result according to the dynamic action under the condition that the dynamic action does not match with the action detection result, the action detection result including an action reference result or a previously detected action detection result.

Abstract: The present disclosure relates to a gesture recognition method, a gesture processing method, and apparatuses. The gesture recognition method includes: detecting the states of fingers included in a hand in an image; determining a state vector of the hand according to the states of the fingers; and determining the gesture of the hand according to the state vector of the hand. In embodiments of the present disclosure, the state vector is determined according to the states of the fingers, and the gesture is determined according to the state vector, thereby achieving high recognition efficiency and strong universality.