research-article

Saliency detection by aggregating complementary background template with foreground information

Authors:

Jianhua CuiAuthors Info & Claims

CASA 2018: Proceedings of the 31st International Conference on Computer Animation and Social Agents

Pages 38 - 42

https://doi.org/10.1145/3205326.3205353

Published: 21 May 2018 Publication History

Abstract

This paper proposes an unsupervised bottom-up saliency detection approach by exploiting novel background template and foreground information. First, a discriminative feature vector is extracted from each super-pixel to cover regional color, contrast and texture information. Then we apply it to get a background based saliency map based on a background template. In order to get more accurate saliency map, we select highly confident compact foreground seeds to compute a foreground based saliency map. After fusing the two saliency maps, the integrated map is refined to achieve the final result. Experimental results show that the proposed algorithm generates high-quality saliency maps against the state-off-the-art saliency detection methods on four publicly available datasets.

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Cited By

Guerra RGarcía Reyes EGonzález Quevedo AVázquez H(2019)FqSD: Full-Quaternion Saliency Detection in ImagesProgress in Pattern Recognition, Image Analysis, Computer Vision, and Applications10.1007/978-3-030-13469-3_54(462-469)Online publication date: 3-Mar-2019
https://doi.org/10.1007/978-3-030-13469-3_54

Index Terms

Saliency detection by aggregating complementary background template with foreground information
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Interest point and salient region detections

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cover image ACM Other conferences

CASA 2018: Proceedings of the 31st International Conference on Computer Animation and Social Agents

May 2018

101 pages

ISBN:9781450363761

DOI:10.1145/3205326

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques
Chinese Academy of Sciences

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 May 2018

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Refereed limited

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National Natural Science Foundation of China
Science and Technology Key Projects of Hunan province

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CASA 2018

CASA 2018: 31st International Conference on Computer Animation and Social Agents

May 21 - 23, 2018

Beijing, China

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CASA 2018 Paper Acceptance Rate 18 of 110 submissions, 16%;

Overall Acceptance Rate 18 of 110 submissions, 16%

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Cited By

Guerra RGarcía Reyes EGonzález Quevedo AVázquez H(2019)FqSD: Full-Quaternion Saliency Detection in ImagesProgress in Pattern Recognition, Image Analysis, Computer Vision, and Applications10.1007/978-3-030-13469-3_54(462-469)Online publication date: 3-Mar-2019
https://doi.org/10.1007/978-3-030-13469-3_54

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