Activity Segmentation of Infrared Images Using Fuzzy Clustering Techniques

Tanvi Banerjee; James M. Keller; Zhongna Zhou; Marjorie Skubic; Erik Stone

Activity Segmentation of Infrared Images Using Fuzzy Clustering Techniques

Tanvi Banerjee, James M. Keller, Zhongna Zhou, Marjorie Skubic, Erik Stone

Wright State University

Research output: Contribution to conference › Presentation

Abstract

Every year, many older adults are at risk for falling, especially in the dark. Infrared lighting provides a nonintrusive lighting in the dark and our research shows a technique of segmenting human activities using fuzzy clustering of image moments even in the dark. While our research is still in the preliminary stages, it shows promise of being able to detect several different activities and in the future might prevent several falls from taking place.

Original language	American English
State	Published - May 1 2011
Event	Proceedings of the 2011 World Conference on Soft Computing - Duration: May 1 2011 → …

Conference

Conference	Proceedings of the 2011 World Conference on Soft Computing
Period	5/1/11 → …

Disciplines

Bioinformatics
Communication
Communication Technology and New Media
Computer Sciences
Databases and Information Systems
Life Sciences
OS and Networks
Physical Sciences and Mathematics
Science and Technology Studies
Social and Behavioral Sciences

Access to Document

https://www.eldertech.missouri.edu/wp-content/uploads/2016/07/Activity-Segmentation-of-Infrared-Images.pdf

Cite this

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title = "Activity Segmentation of Infrared Images Using Fuzzy Clustering Techniques",

abstract = " Every year, many older adults are at risk for falling, especially in the dark. Infrared lighting provides a nonintrusive lighting in the dark and our research shows a technique of segmenting human activities using fuzzy clustering of image moments even in the dark. While our research is still in the preliminary stages, it shows promise of being able to detect several different activities and in the future might prevent several falls from taking place.",

author = "Tanvi Banerjee and Keller, {James M.} and Zhongna Zhou and Marjorie Skubic and Erik Stone",

year = "2011",

month = may,

day = "1",

language = "American English",

note = "Proceedings of the 2011 World Conference on Soft Computing ; Conference date: 01-05-2011",

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TY - CONF

T1 - Activity Segmentation of Infrared Images Using Fuzzy Clustering Techniques

AU - Banerjee, Tanvi

AU - Keller, James M.

AU - Zhou, Zhongna

AU - Skubic, Marjorie

AU - Stone, Erik

PY - 2011/5/1

Y1 - 2011/5/1

N2 - Every year, many older adults are at risk for falling, especially in the dark. Infrared lighting provides a nonintrusive lighting in the dark and our research shows a technique of segmenting human activities using fuzzy clustering of image moments even in the dark. While our research is still in the preliminary stages, it shows promise of being able to detect several different activities and in the future might prevent several falls from taking place.

AB - Every year, many older adults are at risk for falling, especially in the dark. Infrared lighting provides a nonintrusive lighting in the dark and our research shows a technique of segmenting human activities using fuzzy clustering of image moments even in the dark. While our research is still in the preliminary stages, it shows promise of being able to detect several different activities and in the future might prevent several falls from taking place.

UR - https://corescholar.libraries.wright.edu/knoesis/1113

UR - https://www.eldertech.missouri.edu/wp-content/uploads/2016/07/Activity-Segmentation-of-Infrared-Images.pdf

M3 - Presentation

T2 - Proceedings of the 2011 World Conference on Soft Computing

Y2 - 1 May 2011

ER -

Activity Segmentation of Infrared Images Using Fuzzy Clustering Techniques

Abstract

Conference

Disciplines

Access to Document

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