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2020 | OriginalPaper | Chapter

Old Man Fall Detection Based on Surveillance Video Object Tracking

Authors : Zhao Qiu, Xiaoquan Liang, Qiaoqiao Chen, Xiangsheng Huang, Yiping Wang

Published in: Parallel Architectures, Algorithms and Programming

Publisher: Springer Singapore

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Abstract

Image recognition technology based on deep learning has made great progress, which makes object detection technology work in many fields. The number of elderly people in China has risen year by year, proclaiming the arrival of an aging society. “The old man can’t fall” is a consensus. Using object detection algorithm to detect the fall of the elderly is a research hotspot in the field of object detection. Through the analysis of the object detection algorithm and the object tracking algorithm, Deep-sort and YOLOv3 algorithms are used to achieve the real-time fall detection of the surveillance video. The experimental results prove that combined with YOLOv3 and the Deep-sort algorithms can detect the fall of the elderly.

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Metadata
Title
Old Man Fall Detection Based on Surveillance Video Object Tracking
Authors
Zhao Qiu
Xiaoquan Liang
Qiaoqiao Chen
Xiangsheng Huang
Yiping Wang
Copyright Year
2020
Publisher
Springer Singapore
Book
Parallel Architectures, Algorithms and Programming

Print ISBN: 978-981-15-2766-1

Electronic ISBN: 978-981-15-2767-8

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-981-15-2767-8_15