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The study of skeleton description reduction in the human fall-detection task
O.S. Seredin 1, A.V. Kopylov 1, E.E. Surkov 1

1 Tula State University, 300012, Tula, Russia, Lenin Ave. 92

 PDF, 2296 kB

DOI: 10.18287/2412-6179-CO-753

Pages: 951-958.

Full text of article: English language.

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.

Citation:
Seredin OS, Kopylov AV, Surkov EE. The study of skeleton description reduction in the human fall-detection task. Computer Optics 2020; 44(6): 951-958. DOI: 10.18287/2412-6179-CO-753.

Acknowledgements:
The work is supported by the Russian Fund for Basic Research, grants 18-07-00942, 18-07-01087, 20-07-00441. The results of the research project are published with the financial support of Tula State University within the framework of the scientific project 2019-21NIR. The part of the research is carried out using the equipment of the shared research facilities of HPC computing resources at Lomonosov Moscow State University.

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