Human body action reconstruction system and method based on multi-view vision and action training system

Abstract

The invention discloses a human body action reconstruction system and method based on multi-view vision and an action training system. The method comprises: capturing an action image of the target human body based on the at least two monocular cameras after correction; performing human body two-dimensional articulation point identification on the action image on a two-dimensional image; and reconstructing the three-dimensional motion of the target human body on the basis of the human body two-dimensional joint points. A user does not need to wear a specially-made optical capture garment or assemble a corresponding sensor, and the technical problem that an existing depth camera human body three-dimensional motion recognition method is high in application scene requirement and low in recognition accuracy in a complex application scene is solved.

Description

technical field [0001] The present application relates to the technical field of motion recognition, in particular to a multi-eye vision-based human motion reconstruction system, method and motion training system. Background technique [0002] With the development of artificial intelligence, human body posture recognition technology has made important breakthroughs on the basis of larger data sets and powerful computing capabilities available in the era of big data. [0003] The existing 3D human action recognition method is to use optical capture technology to capture the 3D action of the target human body for action recognition. The user wears a special optical capture suit with optical marks or a corresponding detection sensor to obtain the corresponding mark position to generate a spatial relative position, thereby constructing 3D model of the human body for action recognition. The method of using optical capture technology to capture the three-dimensional motion of the...

AI Technical Summary

Problems solved by technology

[0004] The purpose of this application is to provide a human action reconstruction system, method and action training system based on multi-eye vision, which is used to solve the existing three-dimensional human action recognition method that requires the user to wear a special optical capture suit or assemble a corresponding sensor. Troublesome, and the user has a heavy load, which causes inconvenience to movement training and technical problems that affect user experience

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