Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/1750
Title: A smart vision sensor for detecting risk factors of a toddler's fall in a home environment
Authors: Na, H
Qin, SF
Wright, D
Keywords: Computer vision;Image motion analysis;Image sensors
Issue Date: 2007
Publisher: IEEE
Citation: Proceedings of the 2007 IEEE International conference on Networking, Sensing and Control, London, UK, 15-17 April 2007. pp. 656-661.
Abstract: This paper presents a smart vision sensor for detecting risk factors of a toddler's fall in an indoor home environment assisting parents' supervision to prevent fall injuries. We identified the risk factors by analyzing real fall injury stories and referring to a related organization's suggestions to prevent falls. In order to detect the risk factors using computer vision, two major image processing methods, clutter detection and toddler tracking, were studied with using only one commercial web-camera. For practical purposes, there is no need for a toddler to wear any sensors or markers. The algorithms for detection have been developed, implemented and tested.
URI: http://bura.brunel.ac.uk/handle/2438/1750
DOI: http://dx.doi.org/10.1109/ICNSC.2007.372857
ISBN: 1-4244-1076-2
Appears in Collections:Design
Publications
Brunel Design School Research Papers



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