A review of recent texture segmentation and feature extraction techniques
CVGIP: Image Understanding
Multiresolution sampling procedure for analysis and synthesis of texture images
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature Detection with Automatic Scale Selection
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Saliency, Scale and Image Description
International Journal of Computer Vision
Object-based visual attention for computer vision
Artificial Intelligence
The steerable pyramid: a flexible architecture for multi-scale derivative computation
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol. 3)-Volume 3 - Volume 3
Image Retrieval Based on Regions of Interest
IEEE Transactions on Knowledge and Data Engineering
Automatic browsing of large pictures on mobile devices
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Contrast-based image attention analysis by using fuzzy growing
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Automatic thumbnail cropping and its effectiveness
Proceedings of the 16th annual ACM symposium on User interface software and technology
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Generalized principal component analysis (gpca): an algebraic geometric approach to subspace clustering and motion segmentation
Region-of-interest based image resolution adaptation for MPEG-21 digital item
Proceedings of the 12th annual ACM international conference on Multimedia
An Attention-Based Approach to Content-Based Image Retrieval
BT Technology Journal
Robust subspace analysis for detecting visual attention regions in images
Proceedings of the 13th annual ACM international conference on Multimedia
Selective visual attention enables learning and recognition of multiple objects in cluttered scenes
Computer Vision and Image Understanding - Special issue: Attention and performance in computer vision
Gaze-based interaction for semi-automatic photo cropping
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Attention-driven image interpretation with application to image retrieval
Pattern Recognition
Geometric and photometric invariant distinctive regions detection
Information Sciences: an International Journal
Is bottom-up attention useful for object recognition?
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Robust subspace clustering by combined use of kNND metric and SVD algorithm
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Generalized principal component analysis (GPCA)
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Color in image and video processing: most recent trends and future research directions
Journal on Image and Video Processing - Color in Image and Video Processing
Attention driven visual processing for an interactive dialog robot
Proceedings of the 2009 ACM symposium on Applied Computing
Extracting salient visual attention regions by color contrast and wavelet transformation
ISCIT'09 Proceedings of the 9th international conference on Communications and information technologies
A critical review of selective attention: an interdisciplinary perspective
Artificial Intelligence Review
Efficient region-of-interest scalable video coding with adaptive bit-rate control
Advances in Multimedia
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In this paper, we describe a new framework to extract visual attention regions in images using robust subspace estimation and analysis techniques. We use simple features like hue and intensity endowed with scale adaptivity in order to represent smooth and textured areas in an image. A polar transformation maps homogeneity in the features into a linear subspace that also encodes spatial information of a region. A new subspace estimation algorithm based on the Generalized Principal Component Analysis (GPCA) is proposed to estimate multiple linear subspaces. Sensitivity to outliers is achieved by weighted least squares estimate of the subspaces in which weights calculated from the distribution of K nearest neighbors are assigned to data points. Iterative refinement of the weights is proposed to handle the issue of estimation bias when the number of data points in each subspace is very different. A new region attention measure is defined to calculate the visual attention of each region by considering both feature contrast and spatial geometric properties of the regions. Compared with existing visual attention detection methods, the proposed method directly measures global visual attention at the region level as opposed to pixel level.