Limb movement recognition method and device, computer equipment and storage medium

Abstract

The invention discloses a body movement recognition method and device, computer equipment and a storage medium, and belongs to the field of image recognition. The method comprises the following steps: acquiring a target time sequence picture set, wherein the target time sequence picture set is a picture set of a group of limb actions with a time sequence; sequentially inputting the target time sequence picture set into a first network to obtain a target tensor output by the first network, wherein the first network is used for processing the target time sequence picture into a feature matrix, and the target tensor is used for representing a feature matrix set corresponding to the target time sequence picture set; inputting the target tensor into a second network to obtain a limb movement recognition result; extracting at least one sub-tensor from the target tensor, inputting the sub-tensor into the second network to obtain an action category probability corresponding to each sub-tensor, and obtaining a limb action recognition result according to weighted summation. According to the technical scheme, the problem that the accuracy is low due to the fact that the continuity of actions is inconsistent during limb recognition can be solved.

Description

technical field [0001] The invention relates to the field of image recognition, in particular to a body movement recognition method, device, computer equipment and storage medium. Background technique [0002] With the research and progress of artificial intelligence technology, artificial intelligence technology has been researched and applied in many fields, such as smart devices and other fields, and action recognition technology can enable smart devices to understand the actions of interactive objects and make corresponding responses. Body movements trigger certain functions of smart devices, etc. Body movements are the key technology to realize intelligent interaction. [0003] Existing technologies usually use an analysis method based on Long Short-Term Memory (LSTM, Long Short-Term Memory). However, this method’s grasp of the duration of time series pictures is controlled by the memory module in LSTM, and it is usually difficult to guide the network to target Therefo...

AI Technical Summary

Problems solved by technology

[0004] Based on this, the embodiment of the present application provides a body movement recognition method, device, computer equip

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