A smart vision sensor for detecting risk factors of a toddler's fall in a home environment

Hana Na; Sheng-feng Qin; David Wright

doi:10.1109/ICNSC.2007.372857

A smart vision sensor for detecting risk factors of a toddler's fall in a home environment

Hana Na, Sheng-feng Qin, David Wright

Design Department

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

4 Citations (Scopus)

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.

Original language	English
Title of host publication	Proceedings of the 2007 IEEE International Conference on Networking, Sensing and Control
Place of Publication	Piscataway, NJ
Publisher	IEEE
Pages	656-661
ISBN (Print)	1-4244-1076-2
DOIs	https://doi.org/10.1109/ICNSC.2007.372857
Publication status	Published - Apr 2007
Event	2007 IEEE International Conference on Networking, Sensing and Control - London Duration: 1 Apr 2007 → …

Conference

Conference	2007 IEEE International Conference on Networking, Sensing and Control
Period	1/04/07 → …

Keywords

computer vision
image motion analysis
image sensors

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10.1109/ICNSC.2007.372857

Cite this

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title = "A smart vision sensor for detecting risk factors of a toddler's fall in a home environment",

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.",

keywords = "computer vision, image motion analysis, image sensors",

author = "Hana Na and Sheng-feng Qin and David Wright",

year = "2007",

month = apr,

doi = "10.1109/ICNSC.2007.372857",

language = "English",

isbn = "1-4244-1076-2",

pages = "656--661",

booktitle = "Proceedings of the 2007 IEEE International Conference on Networking, Sensing and Control",

publisher = "IEEE",

address = "United States",

note = "2007 IEEE International Conference on Networking, Sensing and Control ; Conference date: 01-04-2007",

}

Na, H, Qin, S & Wright, D 2007, A smart vision sensor for detecting risk factors of a toddler's fall in a home environment. in Proceedings of the 2007 IEEE International Conference on Networking, Sensing and Control. IEEE, Piscataway, NJ, pp. 656-661, 2007 IEEE International Conference on Networking, Sensing and Control, 1/04/07. https://doi.org/10.1109/ICNSC.2007.372857

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T1 - A smart vision sensor for detecting risk factors of a toddler's fall in a home environment

AU - Na, Hana

AU - Qin, Sheng-feng

AU - Wright, David

PY - 2007/4

Y1 - 2007/4

N2 - 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.

AB - 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.

KW - computer vision

KW - image motion analysis

KW - image sensors

U2 - 10.1109/ICNSC.2007.372857

DO - 10.1109/ICNSC.2007.372857

M3 - Chapter

SN - 1-4244-1076-2

SP - 656

EP - 661

BT - Proceedings of the 2007 IEEE International Conference on Networking, Sensing and Control

PB - IEEE

CY - Piscataway, NJ

T2 - 2007 IEEE International Conference on Networking, Sensing and Control

Y2 - 1 April 2007

ER -

A smart vision sensor for detecting risk factors of a toddler's fall in a home environment

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