International Journal of Computer Vision
Context-free attentional operators: the generalized symmetry transform
International Journal of Computer Vision - Special issue on qualitative vision
A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Finding salient regions in images: nonparametric clustering for image segmentation and grouping
Computer Vision and Image Understanding - Special issue on content-based access for image and video libraries
Classification of scene photographs from local orientations features
Pattern Recognition Letters - Selected papers from the 11th scandinavian conference on image analysis
Saliency, Scale and Image Description
International Journal of Computer Vision
Biologically Inspired Saliency Map Model for Bottom-up Visual Attention
BMCV '02 Proceedings of the Second International Workshop on Biologically Motivated Computer Vision
Contrast-based image attention analysis by using fuzzy growing
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Focus-of-Attention from Local Color Symmetries
IEEE Transactions on Pattern Analysis and Machine Intelligence
Region-of-interest based image resolution adaptation for MPEG-21 digital item
Proceedings of the 12th annual ACM international conference on Multimedia
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
Robust subspace analysis for detecting visual attention regions in images
Proceedings of the 13th annual ACM international conference on Multimedia
Boosting Color Saliency in Image Feature Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Assessing the contribution of color in visual attention
Computer Vision and Image Understanding - Special issue: Attention and performance in computer vision
A Coherent Computational Approach to Model Bottom-Up Visual Attention
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Integrated Model of Top-Down and Bottom-Up Attention for Optimizing Detection Speed
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Visual attention based image browsing on mobile devices
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
Visual attention detection in video sequences using spatiotemporal cues
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
2006 Special Issue: Modeling attention to salient proto-objects
Neural Networks
Salient region detection and segmentation
ICVS'08 Proceedings of the 6th international conference on Computer vision systems
Goal-directed search with a top-down modulated computational attention system
PR'05 Proceedings of the 27th DAGM conference on Pattern Recognition
Salient region detection using weighted feature maps based on the human visual attention model
PCM'04 Proceedings of the 5th Pacific Rim Conference on Advances in Multimedia Information Processing - Volume Part II
A Rule Based Technique for Extraction of Visual Attention Regions Based on Real-Time Clustering
IEEE Transactions on Multimedia
Color-Based Image Salient Region Segmentation Using Novel Region Merging Strategy
IEEE Transactions on Multimedia
Unsupervised extraction of visual attention objects in color images
IEEE Transactions on Circuits and Systems for Video Technology
Improved saliency detection based on superpixel clustering and saliency propagation
Proceedings of the international conference on Multimedia
Random walks on graphs for salient object detection in images
IEEE Transactions on Image Processing
Travelmedia: An intelligent management system for media captured in travel
Journal of Visual Communication and Image Representation
REM: relational entropy-based measure of saliency
Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing
Bottom-up saliency detection model based on amplitude spectrum
MMM'11 Proceedings of the 17th international conference on Advances in multimedia modeling - Volume Part I
Unsupervised feature selection for salient object detection
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part II
Salient region detection by jointly modeling distinctness and redundancy of image content
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part II
Saliency density maximization for object detection and localization
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
Spatiotemporal saliency detection and salient region determination for H.264 videos
Journal of Visual Communication and Image Representation
Salient object detection based on regions
Multimedia Tools and Applications
Saliency detection in computer rendered images based on object-level contrast
Journal of Visual Communication and Image Representation
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We present a robust salient region detection framework based on the color and orientation distribution in images. The proposed framework consists of a color saliency framework and an orientation saliency framework. The color saliency framework detects salient regions based on the spatial distribution of the component colors in the image space and their remoteness in the color space. The dominant hues in the image are used to initialize an expectation-maximization (EM) algorithm to fit a Gaussian mixture model in the hue-saturation (H-S) space. The mixture of Gaussians framework in H-S space is used to compute the inter-cluster distance in the H-S domain as well as the relative spread among the corresponding colors in the spatial domain. Orientation saliency framework detects salient regions in images based on the global and local behavior of different orientations in the image. The oriented spectral information from the Fourier transform of the local patches in the image is used to obtain the local orientation histogram of the image. Salient regions are further detected by identifying spatially confined orientations and with the local patches that possess high orientation entropy contrast. The final saliency map is selected as either color saliency map or orientation saliency map by automatically identifying which of the maps leads to the correct identification of the salient region. The experiments are carried out on a large image database annotated with "ground-truth" salient regions, provided by Microsoft Research Asia, which enables us to conduct robust objective level comparisons with other salient region detection algorithms.