Human body action hierarchical identification method based on pyroelectric infrared detection

Abstract

A human body action hierarchical identification method based on pyroelectric infrared detection includes: arrangement of experimental facilities, adopting a single pyroelectric infrared (PIR) sensor with the surface additionally covered by a Fresnel lens, arranging the height of the sensor away from the ground and the vertical distance D between the sensor and a human body; human body action data collection; feature extraction, extracting feature parameters of different actions through fast Fourier transform and wavelet packet analysis according to collected characteristics of human body actions of different signals; hierarchical identification, adopting features extracted in step 3 as the feature parameters and separate the feature parameters one to one; and assorting process achievement through a K mean value clustering algorithm, adopting the 5-fold cross-validation algorithm in the sorting process to estimate a training model considering that pyroelectric signals of different human bodies have certain individual differences. The human body action hierarchical identification method based on pyroelectric infrared detection is high in accuracy, can provide a new idea for processing of pyroelectric signals, and further is applied to the fields including the security system, smart home and man-machine interaction.

Description

Technical field [0001] The invention relates to a hierarchical recognition method of human body movements. In particular, it relates to a hierarchical recognition method of human movement based on pyroelectric infrared detection, which uses fast Fourier transform and wavelet packet analysis to extract the movement characteristics of different actions according to the characteristics of the pyroelectric signals of different actions. Background technique [0002] As computing is penetrating and affecting all aspects of people's lives, identifying human actions and behaviors based on sensor data has gradually become a very active research field in "human-centered computing". Human motion analysis has broad application prospects and potential economic value in advanced human-computer interaction, security monitoring, video conferencing, medical diagnosis, and content-based image storage and retrieval, which inspires a large number of domestic and foreign scientific researchers and re...

AI Technical Summary

Problems solved by technology

At present, the use of pyroelectric information for human action recognition is still rare in research at home and abroad: Yang Jing of Tsinghua University and others used a single PIR sensor to detect the pyroelectricity of a subject's two actions of standing still and jumping. Signal, through the analysis and processing of the signal, the monitoring and identification of these two actions are realized, but the situation of different subjects and different action modes has not been considered

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