Quantitative Analysis of Human-Model Agreement in Visual Saliency Modeling: A Comparative Study

@article{Borji2013QuantitativeAO,
  title={Quantitative Analysis of Human-Model Agreement in Visual Saliency Modeling: A Comparative Study},
  author={A. Borji and Dicky N. Sihite and L. Itti},
  journal={IEEE Transactions on Image Processing},
  year={2013},
  volume={22},
  pages={55-69}
}
Visual attention is a process that enables biological and machine vision systems to select the most relevant regions from a scene. Relevance is determined by two components: 1) top-down factors driven by task and 2) bottom-up factors that highlight image regions that are different from their surroundings. The latter are often referred to as “visual saliency.” Modeling bottom-up visual saliency has been the subject of numerous research efforts during the past 20 years, with many successful… Expand
529 Citations
Human Visual System-Based Saliency Detection for High Dynamic Range Content
  • 31
Examining visual saliency prediction in naturalistic scenes
  • 4
  • Highly Influenced
Examining Visual Saliency Prediction in Naturalistic Scenes Conference
  • Highly Influenced
  • PDF
What stands out in a scene? A study of human explicit saliency judgment
  • 106
  • PDF
A Benchmark of Computational Models of Saliency to Predict Human Fixations in Videos
  • 2
  • Highly Influenced
  • PDF
On computational modeling of visual saliency: Examining what’s right, and what’s left
  • 65
  • PDF
CAT2000: A Large Scale Fixation Dataset for Boosting Saliency Research
  • 165
  • PDF
Fixation prediction with a combined model of bottom-up saliency and vanishing point
  • 10
  • PDF
Information-theoretic model comparison unifies saliency metrics
  • 102
  • PDF
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 110 REFERENCES
Predicting visual fixations on video based on low-level visual features
  • 256
  • PDF
Learning a saliency map using fixated locations in natural scenes.
  • 260
  • PDF
Beyond bottom-up: Incorporating task-dependent influences into a computational model of spatial attention
  • R. J. Peters, L. Itti
  • Computer Science
  • 2007 IEEE Conference on Computer Vision and Pattern Recognition
  • 2007
  • 255
  • PDF
Assessing the contribution of color in visual attention
  • 121
  • PDF
State-of-the-Art in Visual Attention Modeling
  • A. Borji, L. Itti
  • Computer Science, Medicine
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2013
  • 1,477
  • PDF
Probabilistic Multi-Task Learning for Visual Saliency Estimation in Video
  • 140
  • PDF
Esaliency (Extended Saliency): Meaningful Attention Using Stochastic Image Modeling
  • 156
  • PDF
SUN: A Bayesian framework for saliency using natural statistics.
  • 1,156
  • PDF
...
1
2
3
4
5
...