A human motion recognition method based on multi-sensor data fusion

Abstract

The invention relates to the field of human body motion recognition, and provides a human body motion recognition method based on multi-sensor data fusion. The method comprises the following steps: human body motion data are collected by using N inertial sensor nodes respectively fixed at different parts of the human body; sliding window segmentation technology is used to segment the human motiondata collected from each sensor node to obtain multiple motion data segments of each sensor node; feature extraction is carried out on the motion data segment of each sensor node to obtain the corresponding feature vector; an RLDA algorithm is used to reduce the dimension of eigenvectors of each sensor node; the reduced dimension eigenvector of each sensor node is used as training data for parameter training and modeling, and the corresponding hierarchical fusion model is obtained; using the hierarchical fusion model, human motion recognition is carried out. The invention can effectively overcome the drawbacks of the single classifier in the identification process, and can effectively improve the human motion identification accuracy.

Description

technical field [0001] The invention relates to the field of human motion recognition, in particular to a human motion recognition method based on multi-sensor data fusion. Background technique [0002] Human action recognition technology is a new human-computer interaction method that has emerged in recent decades, and it has gradually become a hot issue studied by scholars at home and abroad. Human body movements mainly refer to the way the human body moves, as well as people's responses to the environment or objects. The human body describes or expresses complex human movements through complex movements of the limbs. It can be said that most of the actions of the human body need to be reflected through the movement of the body limbs. It becomes a very effective way to analyze the human body's motion by studying and exploring the human body's motion. Human action recognition based on inertial sensors is an emerging research field in the field of pattern recognition. Its ...

AI Technical Summary

Problems solved by technology

[0004] The present invention mainly solves technical problems such as the single classification algorithm in the prior art cannot be applied to the recognition of all human actions, and the single classifier has certain decision-making errors, etc., and proposes a human action recognition method based on multi-sensor data fusion, which can effectively To overcome the disadvantages of single classifier in the recognition process, the recognition result obtained by using the layered fusion model proposed by the present invention is obviously better than the traditional recognition method

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