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Authors: David Geisler ; Wolfgang Fuhl ; Thiago Santini and Enkelejda Kasneci

Affiliation: University of Tübingen, Germany

ISBN: 978-989-758-225-7

Keyword(s): Saliency Sandbox, Feature Maps, Attention Maps, Saliency Maps, Bottom Up.

Related Ontology Subjects/Areas/Topics: Color and Texture Analyses ; Computer Vision, Visualization and Computer Graphics ; Early and Biologically-Inspired Vision ; Image and Video Analysis ; Image Formation and Preprocessing ; Image Generation Pipeline: Algorithms and Techniques ; Visual Attention and Image Saliency

Abstract: Saliency maps are used to predict the visual stimulus raised from a certain region in a scene. Most approaches to calculate the saliency in a scene can be divided into three consecutive steps: extraction of feature maps, calculation of activation maps, and the combination of activation maps. In the past two decades, several new saliency estimation approaches have emerged. However, most of these approaches are not freely available as source code, thus requiring researchers and application developers to reimplement them. Moreover, others are freely available but use different platforms for their implementation. As a result, employing, evaluating, and combining existing approaches is time consuming, costly, and even error-prone (e.g., when reimplementation is required). In this paper, we introduce the Saliency Sandbox, a framework for the fast implementation and prototyping of saliency maps, which employs a flexible architecture that allows designing new saliency maps by combining existi ng and new approaches such as Itti & Koch, GBVS, Boolean Maps and many more. The Saliency Sandbox comes with a large set of implemented feature extractors as well as some of the most popular activation approaches. The framework core is written in C++; nonetheless, interfaces for Matlab and Simulink allow for fast prototyping and integration of already existing implementations. Our source code is available at: www.ti.uni-tuebingen.de/perception. (More)

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Paper citation in several formats:
Geisler, D.; Fuhl, W.; Santini, T. and Kasneci, E. (2017). Saliency Sandbox - Bottom-up Saliency Framework.In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017) ISBN 978-989-758-225-7, pages 657-664. DOI: 10.5220/0006272306570664

@conference{visapp17,
author={David Geisler. and Wolfgang Fuhl. and Thiago Santini. and Enkelejda Kasneci.},
title={Saliency Sandbox - Bottom-up Saliency Framework},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017)},
year={2017},
pages={657-664},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006272306570664},
isbn={978-989-758-225-7},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017)
TI - Saliency Sandbox - Bottom-up Saliency Framework
SN - 978-989-758-225-7
AU - Geisler, D.
AU - Fuhl, W.
AU - Santini, T.
AU - Kasneci, E.
PY - 2017
SP - 657
EP - 664
DO - 10.5220/0006272306570664

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