Modeling Bottom-Up Visual Attention for Color Images

Congyan LANG  De XU  Ning LI  

IEICE TRANSACTIONS on Information and Systems   Vol.E91-D   No.3   pp.869-872
Publication Date: 2008/03/01
Online ISSN: 1745-1361
DOI: 10.1093/ietisy/e91-d.3.869
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Image Processing and Video Processing
visual attention,  color space,  feature extraction,  salient points,  salient map,  

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Modeling visual attention provides an alternative methodology to image description in many applications such as adaptive content delivery and image retrieval. In this paper, we propose a robust approach to the modeling bottom-up visual attention. The main contributions are twofold: 1) We use a principal component analysis (PCA) to transform the RGB color space into three principal components, which intrinsically leads to an opponent representation of colors to ensure good saliency analysis. 2) A practicable framework for modeling visual attention is presented based on a region-level reliability analysis for each feature map. And then the salient map can be robustly generated for a variety of nature images. Experiments show that the proposed algorithm is effective and can characterize the human perception well.