The study of skeleton description reduction in the human fall-detection task Article Swipe

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Oleg Seredin , Andrey Kopylov , Egor Surkov ·

YOU? · · 2020 · Open Access · · DOI: https://doi.org/10.18287/2412-6179-co-753

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.

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Human Skeleton

Computer Science

Artificial Intelligence

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Skeleton (computer programming) Human skeleton Computer science Reduction (mathematics) Artificial intelligence Computer vision Task (project management) RGB color model Key (lock) Pattern recognition (psychology) Computer security Mathematics Engineering Systems engineering Programming language Geometry

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Type: article
Language: en
Landing Page: https://doi.org/10.18287/2412-6179-co-753
PDF: http://computeroptics.ru/KO/PDF/KO44-6/440613.pdf
OA Status: diamond
Cited By: 7
References: 21
Related Works: 10
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DOI: https://doi.org/10.18287/2412-6179-co-753

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Title: The study of skeleton description reduction in the human fall-detection task

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Language: en

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Publication year: 2020

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Publication date: 2020-12-01

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Authors: Oleg Seredin, Andrey Kopylov, Egor Surkov

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Landing page: https://doi.org/10.18287/2412-6179-co-753

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Concepts: Skeleton (computer programming), Human skeleton, Computer science, Reduction (mathematics), Artificial intelligence, Computer vision, Task (project management), RGB color model, Key (lock), Pattern recognition (psychology), Computer security, Mathematics, Engineering, Systems engineering, Programming language, Geometry

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Cited by: 7

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