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- CHEN Yu
- School of Computer, Wuhan University
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- XIAO Jing
- School of Computer, Wuhan University
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- HU Liuyi
- School of Computer, Wuhan University
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- CHEN Dan
- School of Computer, Wuhan University
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- WANG Zhongyuan
- School of Computer, Wuhan University
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- LI Dengshi
- School of Mathematics and Computer, Jianghan University
抄録
<p>Saliency detection for videos has been paid great attention and extensively studied in recent years. However, various visual scene with complicated motions leads to noticeable background noise and non-uniformly highlighting the foreground objects. In this paper, we proposed a video saliency detection model using spatio-temporal cues. In spatial domain, the location of foreground region is utilized as spatial cue to constrain the accumulation of contrast for background regions. In temporal domain, the spatial distribution of motion-similar regions is adopted as temporal cue to further suppress the background noise. Moreover, a backward matching based temporal prediction method is developed to adjust the temporal saliency according to its corresponding prediction from the previous frame, thus enforcing the consistency along time axis. The performance evaluation on several popular benchmark data sets validates that our approach outperforms existing state-of-the-arts.</p>
収録刊行物
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- IEICE Transactions on Information and Systems
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IEICE Transactions on Information and Systems E101.D (9), 2201-2208, 2018-09-01
一般社団法人 電子情報通信学会
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キーワード
詳細情報 詳細情報について
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- CRID
- 1390845712995186304
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- NII論文ID
- 130007479646
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- ISSN
- 17451361
- 09168532
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- Crossref
- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可