scispace - formally typeset
Journal ArticleDOI

Detection of visual attention regions in images using robust subspace analysis

TLDR
A new framework to extract visual attention regions in images using robust subspace estimation and analysis techniques using simple features like hue and intensity endowed with scale adaptivity in order to represent smooth and textured areas in an image.
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This article is published in Journal of Visual Communication and Image Representation.The article was published on 2008-04-01. It has received 19 citations till now. The article focuses on the topics: Subspace topology & Linear subspace.

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Citations
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An affine invariant salient region detector

TL;DR: In this article, a novel technique for detecting salient regions in an image is described, which is a generalization to affine invariance of the method introduced by Kadir and Brady.
Journal ArticleDOI

Saliency Detection by Multitask Sparsity Pursuit

TL;DR: A solution of multitask sparsity pursuit is proposed to integrate multiple types of features for detecting saliency collaboratively to produce jointly the saliency map with a single inference step and thus produces more accurate and reliable results.
Journal ArticleDOI

Color in image and video processing: most recent trends and future research directions

TL;DR: The most recent trends as well as the state-of-the-art, with a broad survey of the relevant literature, in the main active research areas in color imaging.
Journal ArticleDOI

An Adaptive Computational Model for Salient Object Detection

TL;DR: Extensive quantitative evaluations and comparisons demonstrate that the proposed adaptive computational model to detect the salient object in color images significantly outperforms state-of-the-art methods.
Proceedings ArticleDOI

A Visual Attention Based Approach to Text Extraction

TL;DR: The experimental results demonstrate that the proposed method can effectively extract text information and locate text regions contained in camera-based images and is robust not only for font, size, color, language, space, alignment and complexity of background, but also for perspective distortion and skewed texts embedded in images.
References
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Journal ArticleDOI

Distinctive Image Features from Scale-Invariant Keypoints

TL;DR: This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable matching between different views of an object or scene and can robustly identify objects among clutter and occlusion while achieving near real-time performance.
Journal ArticleDOI

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
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.
Journal ArticleDOI

Feature Detection with Automatic Scale Selection

TL;DR: It is shown how the proposed methodology applies to the problems of blob detection, junction detection, edge detection, ridge detection and local frequency estimation and how it can be used as a major mechanism in algorithms for automatic scale selection, which adapt the local scales of processing to the local image structure.
Proceedings ArticleDOI

Topology matching for fully automatic similarity estimation of 3D shapes

TL;DR: A novel technique is proposed, called Topology Matching, in which similarity between polyhedral models is quickly, accurately, and automatically calculated by comparing Multiresolutional Reeb Graphs (MRGs), which operates well as a search key for 3D shape data sets.
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