Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016)

Saliency detection based on global color and space contrast

Authors
Yajie Zeng, Heng Li, Xinyu Chai
Corresponding Author
Yajie Zeng
Available Online March 2017.
DOI
10.2991/ifmca-16.2017.7How to use a DOI?
Keywords
Saliency detection, global contrast, space contrast
Abstract

Saliency detection acts as an important role in many computer vision tasks. We propose a novel bottom-up, object-level saliency detection method based on global color and space contrast. The proposed method not only considers the global color contrast of the image but also takes the space information into account, leading to an advanced multi-feature combined saliency detection model. Through qualitative and quantitative evaluation, our method consistently outperformed 4 global color (or intensity)–based saliency detection methods, resulting in higher precision.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016)
Series
Advances in Engineering Research
Publication Date
March 2017
ISBN
10.2991/ifmca-16.2017.7
ISSN
2352-5401
DOI
10.2991/ifmca-16.2017.7How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yajie Zeng
AU  - Heng Li
AU  - Xinyu Chai
PY  - 2017/03
DA  - 2017/03
TI  - Saliency detection based on global color and space contrast
BT  - Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016)
PB  - Atlantis Press
SP  - 44
EP  - 47
SN  - 2352-5401
UR  - https://doi.org/10.2991/ifmca-16.2017.7
DO  - 10.2991/ifmca-16.2017.7
ID  - Zeng2017/03
ER  -