Proceedings of the 2015 International Conference on Industrial Technology and Management Science

Comparison Research on Bottom-up Visual Attention Models

Authors
Guiliang Chen, Yongheng Li
Corresponding Author
Guiliang Chen
Available Online November 2015.
DOI
https://doi.org/10.2991/itms-15.2015.131How to use a DOI?
Keywords
Bottom-up; Significance; Visual attention model
Abstract
In recent years, tremendous progresses have been made in research on basic principle of visual cortex information processing, which bring wide attention to bottom-up visual attention system, some models have already been established successfully and been applied to image processing and machine vision. This essay aims to expatiate the seven kinds of currently most representative bottom-up visual significance algorithm models, summarize and compare the advantages and disadvantages of these algorithm models, explain the results of these algorithm models on different categories of images, and provide some thinking and suggestion on possible future development and research direction of bottom-up visual attention models.
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Proceedings
2015 International Conference on Industrial Technology and Management Science
Part of series
Advances in Computer Science Research
Publication Date
November 2015
ISBN
978-94-6252-123-0
ISSN
2352-538X
DOI
https://doi.org/10.2991/itms-15.2015.131How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Guiliang Chen
AU  - Yongheng Li
PY  - 2015/11
DA  - 2015/11
TI  - Comparison Research on Bottom-up Visual Attention Models
BT  - 2015 International Conference on Industrial Technology and Management Science
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/itms-15.2015.131
DO  - https://doi.org/10.2991/itms-15.2015.131
ID  - Chen2015/11
ER  -