Journal Article10.1016/J.PATCOG.2012.02.009
A saliency map based on sampling an image into random rectangular regions of interest
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TL;DR: The proposed approach to compute an image saliency map based on computing local saliencies over random rectangular regions of interest does not require any training bases, operates on the image at the original scale and has only a single parameter which requires tuning.
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About: This article is published in Pattern Recognition. The article was published on 01 Sep 2012. The article focuses on the topics: Eye tracking.
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Citations
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Reduced-Reference Image Quality Assessment in Free-Energy Principle and Sparse Representation
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Salient object detection via global and local cues
TL;DR: A coding-based algorithm for salient object detection that outperforms 22 state-of-the-art methods in terms of three popular evaluation measures, i.e., the Precision and Recall curve, Area Under ROC Curve and F-measure value.
122
A brief survey of visual saliency detection
TL;DR: A detailed overview of the recent progress of saliency detection models in terms of heuristic- based techniques and deep learning-based techniques is demonstrated.
Material based salient object detection from hyperspectral images
TL;DR: A material-based salient object detection method which can effectively distinguish objects with similar perceived color but different spectral responses, and outperforms several existing hyperspectral salient object Detection approaches and the state-of-the-art methods proposed for RGB images.
91
References
A model of saliency-based visual attention for rapid scene analysis
TL;DR: In this article, a visual attention system inspired by the behavior and the neuronal architecture of the early primate visual system is presented, where multiscale image features are combined into a single topographical saliency map.
A model of saliency-based visual attention for rapid scene analysis
Laurent Itti
- 01 Jan 1998
TL;DR: A visual attention system, inspired by the behavior and the neuronal architecture of the early primate visual system, is presented, which breaks down the complex problem of scene understanding by rapidly selecting conspicuous locations to be analyzed in detail.
8.5K
The relationship between Precision-Recall and ROC curves
Jesse Davis,Mark Goadrich +1 more
- 25 Jun 2006
TL;DR: It is shown that a deep connection exists between ROC space and PR space, such that a curve dominates in R OC space if and only if it dominates in PR space.
6.7K
Frequency-tuned salient region detection
Radhakrishna Achanta,Sheila S. Hemami,Francisco J. Estrada,Sabine Süsstrunk +3 more
- 20 Jun 2009
TL;DR: This paper introduces a method for salient region detection that outputs full resolution saliency maps with well-defined boundaries of salient objects that outperforms the five algorithms both on the ground-truth evaluation and on the segmentation task by achieving both higher precision and better recall.
Shifts in selective visual attention: towards the underlying neural circuitry.
Christof Koch,Shimon Ullman +1 more
TL;DR: This study addresses the question of how simple networks of neuron-like elements can account for a variety of phenomena associated with this shift of selective visual attention and suggests a possible role for the extensive back-projection from the visual cortex to the LGN.
4.2K
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