A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Contrast-based image attention analysis by using fuzzy growing
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Combining attention and recognition for rapid scene analysis
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
On the Distribution of Saliency
IEEE Transactions on Pattern Analysis and Machine Intelligence
Context saliency based image summarization
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Salient region detection and segmentation
ICVS'08 Proceedings of the 6th international conference on Computer vision systems
Object of interest detection by saliency learning
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
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This paper presents a novel approach to compute an image saliency map using Centroid Weight map (CWM). Detection of salient image regions is useful for applications like object segmentation and tracking. We developed and tested a method to detect saliency area using 4 features which are color, intensity, Different of Gaussian (DOG), CWM. A key idea is the CWM technique which is followed with N-classes using mean-shift and pixel location variation. The scheme successfully detects saliency region compare with five state-of-the-art saliency region detection method on the 1000 MSRA benchmark database. The proposed method has achieved superior detection accuracy with both higher precision and better recall than traditional method.