Shooting action identification method based on human body skeleton map extraction and grouping motion diagram inquiry

Abstract

The invention discloses a shooting action identification method based on human body skeleton map extraction and grouping motion diagram inquiry. The method includes the following steps: shooting action is acquired into database in advance and is grouped by class, each group constructs a motion diagram, all the actions are rendered into two-dimensional image under multi-angle and then key characteristic is extracted, and image characteristic value of each gesture is calculated. Accurate outline extraction is carried out on shooting picture sequence shot in operation when a person is shooting, characteristic value of skeleton map is calculated, the group in which the gesture most similar to the characteristic value thereof is located is found in database and is taken as a hit group, the group with the most hit in all the skeleton hit of the shooting action is found, then the node where the gesture the most similar to the characteristic value of each skeleton map on the motion diagram is located is found, the points are analyzed and repaired into a continuous section, and the continuous section is taken as action identification result. The invention can fast and accurately identify shooting action only by utilizing an image capturing device.

Description

technical field [0001] The invention relates to a shooting action recognition method based on human body contour image extraction and grouped motion map query, in particular to a method for recognizing a person's shooting action through a motion map composed of a human body contour image and a person's shooting action data. Background technique [0002] Human motion recognition technology has always been a research hotspot in the field of computer vision. Its research purpose is to enable machines to recognize human actions, including body posture, gestures, etc. It is also a brand-new way of human-machine interaction. The interaction does not pass through hardware devices attached to people such as markers, but only through the movement of people themselves. It has a wide range of potential applications in industrial applications. In addition, it also has great prospects and has even been applied in digital entertainment industries such as film and television and games. ...

AI Technical Summary

Problems solved by technology

[0003] In the existing relatively mature motion recognition technology, it mainly relies on some special hardware devices, such as motion capture equipment, but it needs to paste markers on the human body to record the three-dimensional position information of the person to recognize the motion, which is very influential. human interaction experience

Motion recognition without markers is a good alternative. It does not require additional hardware devices for the user. This method mainly relies on the camera to acquire images and then analyze the two-dimensional images to estimate three-dimensional motion and recover three-dimensional from two-dimensional. It is essentially a multi-solution problem, so it is impossible to achieve 100% recognition accuracy, but in some applications (such as interactive games), its recognition accuracy can already meet the requirements

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