A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Saliency, Scale and Image Description
International Journal of Computer Vision
Image Indexing Using Color Correlograms
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Spatial Color Histograms for Content-Based Image Retrieval
ICTAI '99 Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence
Image Signature: Highlighting Sparse Salient Regions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Global contrast based salient region detection
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
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We proposed a computational visual saliency modeling technique. The proposed technique makes use of a color co-occurrence histogram (CCH) that captures not only "how many" but also "where and how" image pixels are composed into a visually perceivable image. Hence the CCH encodes image saliency information that is usually perceived as the discontinuity between an image region or object and its surrounding. The proposed technique has a number of distinctive characteristics: It is fast, discriminative, tolerant to image scale variation, and involves minimal parameter tuning. Experiments over benchmarking datasets show that it predicts fixational eye tracking points accurately and a superior AUC of 71.25 is obtained.