A Co-Saliency Model of Image Pairs

In this paper, we introduce a method to detect co-saliency from an image pair that may have some objects in common. The co-saliency is modeled as a linear combination of the single-image saliency map (SISM) and the multi-image saliency map (MISM). The first term is designed to describe the local att...

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Bibliographic Details
Published in:IEEE transactions on image processing 2011-12, Vol.20 (12), p.3365-3375
Main Authors: Li, Hongliang, Ngan, King Ngi
Format: Article
Language:English
Subjects:
Applied sciences
Attention model
co-saliency
Color
Computational modeling
Exact sciences and technology
Feature extraction
Graphs
Histograms
Image color analysis
Image processing
Image representation
Image segmentation
Image texture
Information, signal and communications theory
Mathematical models
Representations
Signal processing
Similarity
SimRank
Studies
Surface layer
Telecommunications and information theory
Texture
Visualization
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Summary:In this paper, we introduce a method to detect co-saliency from an image pair that may have some objects in common. The co-saliency is modeled as a linear combination of the single-image saliency map (SISM) and the multi-image saliency map (MISM). The first term is designed to describe the local attention, which is computed by using three saliency detection techniques available in literature. To compute the MISM, a co-multilayer graph is constructed by dividing the image pair into a spatial pyramid representation. Each node in the graph is described by two types of visual descriptors, which are extracted from a representation of some aspects of local appearance, e.g., color and texture properties. In order to evaluate the similarity between two nodes, we employ a normalized single-pair SimRank algorithm to compute the similarity score. Experimental evaluation on a number of image pairs demonstrates the good performance of the proposed method on the co-saliency detection task.
ISSN:1057-7149
1941-0042
DOI:10.1109/TIP.2011.2156803