Robust background modeling based on multiscale color description

Kahlil Muchtar; Chih Yang Lin; Li Wei Kang; Chia Hung Yeh

Robust background modeling based on multiscale color description

Kahlil Muchtar, Chih Yang Lin, Li Wei Kang, Chia Hung Yeh

Department of Mechanical Engineering

Research output: Contribution to conference › Paper › peer-review

3 Scopus citations

Abstract

Background subtraction is the basis of object detection and tracking for machine vision systems. Traditional background modeling methods often require complicated computations and are sensitive to illumination changes and shadow interference. In this paper, we propose a multiscale background modeling method, which fully utilizes the color characteristics of each incoming frame. The proposed method is quite efficient and is capable of resisting illumination changes and shadow disturbance. Experimental results show that our method is suitable for real-world scenarios and real-time applications.

Original language	English
Pages	748-751
Number of pages	4
State	Published - 2011
Event	Asia-Pacific Signal and Information Processing Association Annual Summit and Conference 2011, APSIPA ASC 2011 - Xi'an, China Duration: 18 Oct 2011 → 21 Oct 2011

Conference

Conference	Asia-Pacific Signal and Information Processing Association Annual Summit and Conference 2011, APSIPA ASC 2011
Country/Territory	China
City	Xi'an
Period	18/10/11 → 21/10/11

Cite this

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title = "Robust background modeling based on multiscale color description",

abstract = "Background subtraction is the basis of object detection and tracking for machine vision systems. Traditional background modeling methods often require complicated computations and are sensitive to illumination changes and shadow interference. In this paper, we propose a multiscale background modeling method, which fully utilizes the color characteristics of each incoming frame. The proposed method is quite efficient and is capable of resisting illumination changes and shadow disturbance. Experimental results show that our method is suitable for real-world scenarios and real-time applications.",

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T1 - Robust background modeling based on multiscale color description

AU - Muchtar, Kahlil

AU - Lin, Chih Yang

AU - Kang, Li Wei

AU - Yeh, Chia Hung

PY - 2011

Y1 - 2011

N2 - Background subtraction is the basis of object detection and tracking for machine vision systems. Traditional background modeling methods often require complicated computations and are sensitive to illumination changes and shadow interference. In this paper, we propose a multiscale background modeling method, which fully utilizes the color characteristics of each incoming frame. The proposed method is quite efficient and is capable of resisting illumination changes and shadow disturbance. Experimental results show that our method is suitable for real-world scenarios and real-time applications.

AB - Background subtraction is the basis of object detection and tracking for machine vision systems. Traditional background modeling methods often require complicated computations and are sensitive to illumination changes and shadow interference. In this paper, we propose a multiscale background modeling method, which fully utilizes the color characteristics of each incoming frame. The proposed method is quite efficient and is capable of resisting illumination changes and shadow disturbance. Experimental results show that our method is suitable for real-world scenarios and real-time applications.

UR - http://www.scopus.com/inward/record.url?scp=84866844135&partnerID=8YFLogxK

M3 - 會議論文

AN - SCOPUS:84866844135

SP - 748

EP - 751

T2 - Asia-Pacific Signal and Information Processing Association Annual Summit and Conference 2011, APSIPA ASC 2011

Y2 - 18 October 2011 through 21 October 2011

ER -

Robust background modeling based on multiscale color description

Abstract

Conference

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