Multi-View 3D Human Pose Tracking Based on Evolutionary Robot Vision

Wei Quan and Naoyuki Kubota

Graduate School of System Design, Tokyo Metropolitan University
2-6-6 Asahigaoka, Hino, Tokyo 191-0065, Japan

Received:

March 2, 2021

Accepted:

April 30, 2021

Published:

July 20, 2021

Keywords:

three-dimensional pose estimation, evolutionary algorithm, physical exercise monitoring

Abstract

Human life expectancy is at present the maximum in recorded history. However, a disadvantage is that the elderly are increasingly displaying cognitive disabilities. Studies have shown that physical exercises such as calisthenics can potentially prevent disabilities. Meanwhile, existing systems for evaluating human pose focus mainly on accuracy and omit convenience and efficiency. To solve this issue, in this paper, we propose a framework for rapidly estimating three-dimensional human pose from two camera views. It is based on an evolutionary algorithm. This system can be applied straightforwardly to inexpensive smart devices and used to evaluate multiple individuals’ calisthenics with two or more smart devices.

Cite this article as:

W. Quan and N. Kubota, “Multi-View 3D Human Pose Tracking Based on Evolutionary Robot Vision,” J. Adv. Comput. Intell. Intell. Inform., Vol.25 No.4, pp. 432-441, 2021.

Data files:

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