Human Posture Recognition for Estimation of Human Body Condition

Author:

Quan Wei,Woo Jinseok,Toda Yuichiro,Kubota Naoyuki, ,

Abstract

Human posture recognition has been a popular research topic since the development of the referent fields of human-robot interaction, and simulation operation. Most of these methods are based on supervised learning, and a large amount of training information is required to conduct an ideal assessment. In this study, we propose a solution to this by applying a number of unsupervised learning algorithms based on the forward kinematics model of the human skeleton. Next, we optimize the proposed method by integrating particle swarm optimization (PSO) for optimization. The advantage of the proposed method is no pre-training data is that required for human posture generation and recognition. We validate the method by conducting a series of experiments with human subjects.

Publisher

Fuji Technology Press Ltd.

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Research on human posture recognition based on multi-feature fusion chunk sampling particle filtering algorithm;2022 4th International Conference on Frontiers Technology of Information and Computer (ICFTIC);2022-12-02

2. Human Body Posture Recognition Approaches;ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY;2022-06-13

3. Research on Methods of Physical Aided Education Based on Deep Learning;Scientific Programming;2022-05-09

4. Multi-View 3D Human Pose Tracking Based on Evolutionary Robot Vision;Journal of Advanced Computational Intelligence and Intelligent Informatics;2021-07-20

5. A Systematic Review of Location Aware Schemes in the Internet of Things;Sensors;2021-05-06

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3