A Unified Spectral-Domain Approach for Saliency Detection and Its Application to Automatic Object Segmentation

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In this paper, a visual attention model is incorporated for efficient saliency detection, and the salient regions are employed as object seeds for our automatic object segmentation system. In contrast with existing interactive segmentation approaches that require considerable user interaction, the proposed method does not require it, i.e., the segmentation task is fulfilled in a fully automatic manner. First, we introduce a novel unified spectral-domain approach for saliency detection. Our visual attention model originates from a well-known property of the human visual system that the human visual perception is highly adaptive and sensitive to structural information in images rather than nonstructural information. Then, based on the saliency map, we propose an iterative self-adaptive segmentation framework for more accurate object segmentation. Extensive tests on a variety of cluttered natural images show that the proposed algorithm is an efficient indicator for characterizing the human perception and it can provide satisfying segmentation performance.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2012-03
Language
English
Article Type
Article
Keywords

GRAPH CUTS; IMAGE SEGMENTATION; VISUAL-ATTENTION

Citation

IEEE TRANSACTIONS ON IMAGE PROCESSING, v.21, no.3, pp.1272 - 1283

ISSN
1057-7149
DOI
10.1109/TIP.2011.2164420
URI
http://hdl.handle.net/10203/96385
Appears in Collection
EE-Journal Papers(저널논문)
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