Hybrid background modeling for long-term and short-term illumination changes

研究成果: ジャーナルへの寄稿記事

3 引用 (Scopus)

抄録

Background modeling has been widely researched to detect moving objects from image sequences. It is necessary to adapt the background model various changes of illumination condition. Recent years, a hybrid type of background model which consists of more than one background model has been used for object detection since it is very adaptable to illumination changes. In this paper, we also propose a new hybrid type of background model named "Hybrid Spatial-Temporal Background Model". Our model consists of two different kinds of background models. One is pixel-level background model which adapts to long-term illumination changes. The other is spatial-temporal background model which adapts to short-term illumination changes. Our experimental results demonstrate superiority of our method to some related works.

元の言語英語
ジャーナルIEEJ Transactions on Electronics, Information and Systems
130
発行部数9
DOI
出版物ステータス出版済み - 1 1 2010

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All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

これを引用

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title = "Hybrid background modeling for long-term and short-term illumination changes",
abstract = "Background modeling has been widely researched to detect moving objects from image sequences. It is necessary to adapt the background model various changes of illumination condition. Recent years, a hybrid type of background model which consists of more than one background model has been used for object detection since it is very adaptable to illumination changes. In this paper, we also propose a new hybrid type of background model named {"}Hybrid Spatial-Temporal Background Model{"}. Our model consists of two different kinds of background models. One is pixel-level background model which adapts to long-term illumination changes. The other is spatial-temporal background model which adapts to short-term illumination changes. Our experimental results demonstrate superiority of our method to some related works.",
author = "Atsushi Shimada and Rin-Ichiro Taniguchi",
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AB - Background modeling has been widely researched to detect moving objects from image sequences. It is necessary to adapt the background model various changes of illumination condition. Recent years, a hybrid type of background model which consists of more than one background model has been used for object detection since it is very adaptable to illumination changes. In this paper, we also propose a new hybrid type of background model named "Hybrid Spatial-Temporal Background Model". Our model consists of two different kinds of background models. One is pixel-level background model which adapts to long-term illumination changes. The other is spatial-temporal background model which adapts to short-term illumination changes. Our experimental results demonstrate superiority of our method to some related works.

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