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This article is cited in 5 scientific papers (total in 5 papers)
IMAGE PROCESSING, PATTERN RECOGNITION
The study of skeleton description reduction in the human fall-detection task
O. S. Seredin, A. V. Kopylov, E. E. Surkov Tula State University
Abstract:
Accurate and reliable real-time fall detection is a key aspect of any intelligent elderly people care system. A lot of modern RGB-D cameras can provide a skeleton description of a human figure as a compact pose presentation. This makes it possible to use this description for further analysis without access to real video and, thus, to increase the privacy of the whole system. The skeleton description reduction based on the anthropometrical characteristics of a human body is proposed. The experimental study on the TST Fall Detection dataset v2 by the Leave-One-Person-Out method shows that the proposed skeleton description reduction technique provides better recognition quality and increases the overall performance of a Fall-Detection System.
Keywords:
fall detection, human activity detection, skeleton description, RGB-D camera, elderly people care system.
Received: 17.05.2020 Accepted: 17.07.2020
Citation:
O. S. Seredin, A. V. Kopylov, E. E. Surkov
Linking options:
https://www.mathnet.ru/eng/co869
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Abstract page: | 56 | Full-text PDF : | 44 | References: | 10 |
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