Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology

Research of computer image aesthetics’ classification and assessment based on support vector machine

Authors
Jian-liang Xiong, Yan-mei Yang
Corresponding Author
Jian-liang Xiong
Available Online March 2016.
DOI
10.2991/icmmct-16.2016.22How to use a DOI?
Keywords
Support vector machine, Computer image aesthetics; Classification, Evaluation.
Abstract

Computer image aesthetics is an interdisciplinary research field, which covering visual arts, psychology, information theory and other disciplines. And it depends on the image processing and computer vision to solve specific problems. This paper will design a comprehensive computer image aesthetic evaluation model, containing aesthetic categories and scores prediction, which will be realized by SVM classifier and SVR algorithm. Experiments show that the model’s experimental results are in conformity with human aesthetic perception results.

Copyright
© 2016, 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 4th International Conference on Machinery, Materials and Computing Technology
Series
Advances in Engineering Research
Publication Date
March 2016
ISBN
978-94-6252-165-0
ISSN
2352-5401
DOI
10.2991/icmmct-16.2016.22How to use a DOI?
Copyright
© 2016, 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  - Jian-liang Xiong
AU  - Yan-mei Yang
PY  - 2016/03
DA  - 2016/03
TI  - Research of computer image aesthetics’ classification and assessment based on support vector machine
BT  - Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology
PB  - Atlantis Press
SP  - 115
EP  - 120
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmmct-16.2016.22
DO  - 10.2991/icmmct-16.2016.22
ID  - Xiong2016/03
ER  -