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Fall detection based on the gravity vector using a wide-angle camera
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DOI：10.1016/j.eswa.2014.06.045.png)
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Abstract
En 中文
Falls in elderly people are becoming an increasing healthcare problem, since life expectancy and the number of elderly people who live alone have increased over recent decades. If fall detection systems could be installed easily and economically in homes, telecare could be provided to alleviate this problem. In this paper we propose a low cost fall detection system based on a single wide-angle camera. Wide-angle cameras are used to reduce the number of cameras required for monitoring large areas. Using a calibrated video system, two new features based on the gravity vector are introduced for fall detection. These features are: angle between the gravity vector and the line from feet to head of the human and size of the upper body. Additionally, to differentiate between fall events and controlled lying down events the speed of changes in the features is also measured. Our experiments demonstrate that our system is 97% accurate for fall detection. (C) 2014 Elsevier Ltd. All rights reserved.
Keywords:
Fall detection
Artificial vision
Feature selection
Feature extraction
New features based on gravity vector
Monocular camera
Wide-angle camera
Calibration
Low cost
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