Efficient spatiotemporal-attention-driven shot matching
Proceedings of the 15th international conference on Multimedia
Modeling Bottom-Up Visual Attention for Color Images
IEICE - Transactions on Information and Systems
Object motion detection using information theoretic spatio-temporal saliency
Pattern Recognition
Salient region detection by modeling distributions of color and orientation
IEEE Transactions on Multimedia
Complex Zernike moments features for shape-based image retrieval
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans - Special section: Best papers from the 2007 biometrics: Theory, applications, and systems (BTAS 07) conference
Depth-Spatio-Temporal Joint Region-of-Interest Extraction and Tracking for 3D Video
FGIT '09 Proceedings of the 1st International Conference on Future Generation Information Technology
Salient region extraction based on intensity mapping for image retrieval
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Salient region detection and segmentation
ICVS'08 Proceedings of the 6th international conference on Computer vision systems
Multi-view video based multiple objects segmentation using graph cut and spatiotemporal projections
Journal of Visual Communication and Image Representation
Depth perceptual region-of-interest based multiview video coding
Journal of Visual Communication and Image Representation
Crowdsourced automatic zoom and scroll for video retargeting
Proceedings of the international conference on Multimedia
Segmenting salient objects from images and videos
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
Autonomous behavior-based switched top-down and bottom-up visual attention for mobile robots
IEEE Transactions on Robotics
Stereoscopic visual attention-based regional bit allocation optimization for multiview video coding
EURASIP Journal on Advances in Signal Processing
Saliency density maximization for object detection and localization
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
A biologically inspired computational model for image saliency detection
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Combining content-based analysis and crowdsourcing to improve user interaction with zoomable video
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Global salient information maximization for saliency detection
Image Communication
Stereoscopic visual attention model for 3d video
MMM'10 Proceedings of the 16th international conference on Advances in Multimedia Modeling
A novel video salient object extraction method based on visual attention
Image Communication
Two-layer average-to-peak ratio based saliency detection
Image Communication
Color image segmentation based on regional saliency
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part V
Similar region contrast based salient object detection
CVM'12 Proceedings of the First international conference on Computational Visual Media
Saliency detection using joint spatial-color constraint and multi-scale segmentation
Journal of Visual Communication and Image Representation
Salient object detection via color contrast and color distribution
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
Optimal contrast based saliency detection
Pattern Recognition Letters
Multi-spectral dataset and its application in saliency detection
Computer Vision and Image Understanding
Tag-Saliency: Combining bottom-up and top-down information for saliency detection
Computer Vision and Image Understanding
Oscillation analysis for salient object detection
Multimedia Tools and Applications
Neurocomputing
Ensemble dictionary learning for saliency detection
Image and Vision Computing
SalientShape: group saliency in image collections
The Visual Computer: International Journal of Computer Graphics
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This paper proposes a generic model for unsupervised extraction of viewer's attention objects from color images. Without the full semantic understanding of image content, the model formulates the attention objects as a Markov random field (MRF) by integrating computational visual attention mechanisms with attention object growing techniques. Furthermore, we describe the MRF by a Gibbs random field with an energy function. The minimization of the energy function provides a practical way to obtain attention objects. Experimental results on 880 real images and user subjective evaluations by 16 subjects demonstrate the effectiveness of the proposed approach.