Motion recognition method based on segmented mannequin model applied in human-machine cooperation

Abstract

The invention relates to a motion recognition method based on a segmented human body model applied in human-machine cooperation, which uses a Microsoft Kinect V2 sensor to collect human body bone information and obtain joint node coordinates. After preprocessing, the skeletal node sequence is mapped from four dimensions to three dimensions and stored as a point cloud sequence. The mannequin is divided into upper limb, lower limb and trunk. The Boolean eigenvectors and the relative positions of joints are extracted respectively. The key frames are extracted by the Boolean eigenvectors, and thetemplates are matched by the eigenvectors and the dynamic time warping algorithm (DTW algorithm). Finally, the recognition results of the three parts are combined to get the classification of the whole human motion. The present invention not only achieves the purpose of recognizing the whole movement of the human body, but also obtains the description of the movement of the upper limb, the torso and the lower limb of the human body, and can recognize the movement and the behavior of the human body in more detail and accurately, so as to help the robot under the cooperation of the human and themachine to carry out the subsequent task planning.

Description

technical field [0001] The invention belongs to the field of human-computer interaction, and relates to an action recognition method based on a segmented human body model applied in human-computer cooperation. Background technique [0002] With the development of robot technology, the application scenarios of robots are becoming wider and wider, and there are more and more intersections and integrations with other fields. At the same time, there are many scenarios that require collaborative operations between humans and robots. The collaborative operation of robots and humans can not only liberate human labor, but also help humans avoid high-risk operational tasks at certain times. Human-machine cooperation is one of the future development directions of intelligent robots in the future. [0003] Human-machine collaboration emphasizes the leading role of humans. It should enable robots to understand human intentions as accurately as possible under the premise of ensuring saf...

AI Technical Summary

Problems solved by technology

[0004] However, human actions have the characteristics of high complexity, large amount of information, different users may have differences in the same action, different actions may have repetitive gestures, and may have meaningless actions, etc., which makes the recognition of human actions difficult. Big, is a cross topic involving computer vision, pattern recognition, artificial intelligence and other fields

Images