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Co-saliency detection via inter and intra saliency propagation

Ge, Chenjie, 1991 (author)
Chalmers tekniska högskola,Chalmers University of Technology
Fu, Keren, 1988 (author)
Chalmers tekniska högskola,Chalmers University of Technology
Liu, Fanghui (author)
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Bai, Li (author)
Yang, Jie (author)
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 (creator_code:org_t)
2016
2016
English.
In: Signal Processing: Image Communication. - 0923-5965. ; 44, s. 69-83
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • The goal of salient object detection from an image is to extract the regions which capture the attention of the human visual system more than other regions of the image. In this paper a novel method is presented for detecting salient objects from a set of images, known as co-saliency detection. We treat co-saliency detection as a two-stage saliency propagation problem. The first inter-saliency propagation stage utilizes the similarity between a pair of images to discover common properties of the images with the help of a single image saliency map. With the pairwise co-salient foreground cue maps obtained, the second intra-saliency propagation stage refines pairwise saliency detection using a graph-based method combining both foreground and background cues. A new fusion strategy is then used to obtain the co-saliency detection results. Finally an integrated multi-scale scheme is employed to obtain pixel-level co-saliency maps. The proposed method makes use of existing saliency detection models for co-saliency detection and is not overly sensitive to the initial saliency model selected. Extensive experiments on three benchmark databases show the superiority of the proposed co-saliency model against the state-of-the-art methods both subjectively and objectively.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)

Keyword

Inter-saliency propagation
Fusion
Co-saliency detection
Intra-saliency propagation

Publication and Content Type

art (subject category)
ref (subject category)

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