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Binocular Vision Positioning Method for Safety Monitoring of Solitary Elderly

Lihua Zhu1, Yan Zhang1, Yu Wang1,*, Cheire Cheng2

1 School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, 210000, China
2 Department of Electrical and Electronic Engineering, Colorado State University, Colorado, United States

* Corresponding Author: Yu Wang. Email: email

Computers, Materials & Continua 2022, 71(1), 593-609. https://doi.org/10.32604/cmc.2022.022053

Abstract

In nowadays society, the safety of the elderly population is becoming a pressing concern, especially for those who live alone. There might be daily risks such as accidental falling or treatment attack on them. Aiming at these problems, indoor positioning could be a critical way to monitor their states. With the rapidly development of the imaging techniques, wearable and portable cameras are very popular, which could be set on human individual. And in view of the advantages of the visual positioning, the authors propose a binocular visual positioning algorithm to real-timely locate the elderly indoor. In this paper, the imaging model has been established with the corrected image data from the binocular camera; then feature extraction has been completed to provide reference to adjacent image matching based on the binary robust independent elementary feature (BRIEF) descriptor, finally the camera movement and the states of the elderly have been estimated to distinguish their falling risk. In the experiments, the real-sense D435i sensors were adopted as the binocular cameras to obtain indoor images, and three experimental scenarios have been carried out to test the proposed method. The results show that the proposed algorithm can effectively locate the elderly indoor and improve the real-time monitoring capability.

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Cite This Article

L. Zhu, Y. Zhang, Y. Wang and C. Cheng, "Binocular vision positioning method for safety monitoring of solitary elderly," Computers, Materials & Continua, vol. 71, no.1, pp. 593–609, 2022.



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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