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Proceedings ArticleDOI

Gestalt saliency: Salient region detection based on Gestalt principles

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TLDR
A saliency detection method based on Gestalt principles in which mid-level Gestalt concepts for low-level saliency are introduced and two smoothing procedures are proposed to uniformly highlight the salient object.
Abstract
Salient region detection is of great significance in computer vision such as object recognition, image segmentation and image retrieval. However, low-level saliency has certain limitations due to lack of object level information. In this paper, we propose a saliency detection method based on Gestalt principles in which we introduce mid-level Gestalt concepts for low-level saliency. We propose an algorithm based on Gestalt principles of similarity & anomaly to select and suppress the similar background regions, using variance of clusters of image regions. Moreover, we propose two smoothing procedures based on Gestalt principles of similarity & proximity to group near and similar regions and therefore uniformly highlight the salient object. Experimental results on public data set show that our method performs well compared with state-of-the-art approaches.

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Pattern recognition

Journal ArticleDOI

Unsupervised image saliency detection with Gestalt-laws guided optimization and visual attention based refinement

TL;DR: An integrated framework consisting of bottom-up and top-down attention mechanisms that enable attention to be computed at the level of salient objects and/or regions is proposed.
Book ChapterDOI

Teacher Noticing in Various Grade Bands and Contexts: Commentary

TL;DR: In this paper, the authors explore professional noticing in contexts that include both middle and high school pre- and in-service teachers, and examine the professional noticing activities of their participants using different research methodologies.
Journal ArticleDOI

Salient object detection via contrast information and object vision organization cues

TL;DR: This paper proposes to delineate saliency by considering both the contrast and object vision organization, inspired by the Gestalt principles of grouping from the study of visual perception, and demonstrates that the model outperforms the state-of-the-art methods.
Proceedings ArticleDOI

Enhancing Infographics Based on Symmetry Saliency

TL;DR: A new approach to intentionally drawing visual attention for infographic images, in such a way that the corresponding important features naturally pop up in the image by evaluating how much each image edge contributes to the symmetry saliency, and augmenting the corresponding image gradient by solving the Poisson equation.
References
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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.
Journal ArticleDOI

A tutorial on spectral clustering

TL;DR: In this article, the authors present the most common spectral clustering algorithms, and derive those algorithms from scratch by several different approaches, and discuss the advantages and disadvantages of these algorithms.

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

Efficient Graph-Based Image Segmentation

TL;DR: An efficient segmentation algorithm is developed based on a predicate for measuring the evidence for a boundary between two regions using a graph-based representation of the image and it is shown that although this algorithm makes greedy decisions it produces segmentations that satisfy global properties.
Book

Principles of gestalt psychology

K. Koffka
TL;DR: Routledge is now reissuing this prestigious series of 204 volumes originally published between 1910 and 1965, including works by key figures such as C.G. Jung, Sigmund Freud, Jean Piaget, Otto Rank, James Hillman, Erich Fromm, Karen Horney and Susan Isaacs as discussed by the authors.
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