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Proceedings ArticleDOI

Fall Detection from Human Shape and Motion History Using Video Surveillance

C. Rougier, +3 more
- Vol. 2, pp 875-880
TLDR
A new method to detect falls, which are one of the greatest risk for seniors living alone, is proposed, based on a combination of motion history and human shape variation.
Abstract
Nowadays, Western countries have to face the growing population of seniors. New technologies can help people stay at home by providing a secure environment and improving their quality of life. The use of computer vision systems offers a new promising solution to analyze people behavior and detect some unusual events. In this paper, we propose a new method to detect falls, which are one of the greatest risk for seniors living alone. Our approach is based on a combination of motion history and human shape variation. Our algorithm provides promising results on video sequences of daily activities and simulated falls.

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Citations
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Journal ArticleDOI

A survey on fall detection: Principles and approaches

TL;DR: A comprehensive survey of different systems for fall detection and their underlying algorithms is given, divided into three main categories: wearable device based, ambience device based and vision based.
Journal ArticleDOI

Robust Video Surveillance for Fall Detection Based on Human Shape Deformation

TL;DR: A new method is proposed to detect falls by analyzing human shape deformation during a video sequence, which gives very good results (as low as 0% error with a multi-camera setup) compared with other common image processing methods.
Journal ArticleDOI

Video-Based Abnormal Human Behavior Recognition—A Review

TL;DR: The main purpose of this survey is to extensively identify existing methods and characterize the literature in a manner that brings key challenges to attention.
Proceedings ArticleDOI

Approaches and principles of fall detection for elderly and patient

TL;DR: This paper gives a survey of fall detection for elderly and patient, focusing on identifying approaches and principles of the existing fall detection methods, and gives comments on how to improve some algorithms.
Journal ArticleDOI

A Posture Recognition-Based Fall Detection System for Monitoring an Elderly Person in a Smart Home Environment

TL;DR: A novel computer vision-based fall detection system for monitoring an elderly person in a home care application that can achieve a high fall detection rate and a very low false detection rate in a simulated home environment is proposed.
References
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