Open AccessResearch On human motion recognition algorithm based on WLD
Author(s) -
Sun Feng,
Xia Li
Publication year - 2021
Publication title -
international journal of engineering and computer science
Language(s) - English
Resource type - Journals
ISSN - 2319-7242
DOI - 10.18535/ijecs/v10i8.4615
Subject(s) - computer science , wearable computer , algorithm , state (computer science) , activity recognition , bayesian probability , motion (physics) , artificial intelligence , data mining , machine learning , embedded system
With the rapid development of intelligent technology,People’s lives have gradually entered the era of information and intelligentce,Wearable devices are becoming more and more popular,it is easier to use sensors to obtain data,even physiological data,from human body.When large amounts of data are collected by sensors,we can analyze and model them.the values of each characteristic are used to judge the user’s state,then according to the state we can provide users with more accurate and convenient services. In this paper,the data collected by different sensors are used to establish a prediction model and analyze the comparative effect of different recognition algorithms on the test data. The results of the experiment shows that the Bayesian method based on WLD identities the state of the human body better.