A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
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
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
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
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
Video retargeting: automating pan and scan
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Region-based visual attention analysis with its application in image browsing on small displays
Proceedings of the 15th international conference on Multimedia
Scale adaptive visual attention detection by subspace analysis
Proceedings of the 15th international conference on Multimedia
Detection of visual attention regions in images using robust subspace analysis
Journal of Visual Communication and Image Representation
A generic virtual content insertion system based on visual attention analysis
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Image retargeting using mesh parametrization
IEEE Transactions on Multimedia
Salient region detection by modeling distributions of color and orientation
IEEE Transactions on Multimedia
An automatic image browsing technique for small display users
ICACT'09 Proceedings of the 11th international conference on Advanced Communication Technology - Volume 3
Salient region extraction based on intensity mapping for image retrieval
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Probabilistic Multi-Task Learning for Visual Saliency Estimation in Video
International Journal of Computer Vision
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
A color saliency model for salient objects detection in natural scenes
MMM'10 Proceedings of the 16th international conference on Advances in Multimedia Modeling
Multi-operator image retargeting with automatic integration of direct and indirect seam carving
Image and Vision Computing
Oscillation analysis for salient object detection
Multimedia Tools and Applications
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Detecting visually attentive regions of an image is a challenging but useful issue in many multimedia applications. In this paper, we describe a method to extract visual attentive regions in images using subspace estimation and analysis techniques. The image is represented in a 2D space using polar transformation of its features so that each region in the image lies in a 1D linear subspace. A new subspace estimation algorithm based on Generalized Principal Component Analysis (GPCA) is proposed. The robustness of subspace estimation is improved by using weighted least square approximation where weights are calculated from the distribution of K nearest neighbors to reduce the sensitivity of outliers. Then a new region attention measure is defined to calculate the visual attention of each region by considering both feature contrast and geometric properties of the regions. The method has been shown to be effective through experiments to be able to overcome the scale dependency of other methods. Compared with existing visual attention detection methods, it directly measures the global visual contrast at the region level as opposed to pixel level contrast and can correctly extract the attentive region.