skip to main content
10.1145/3095713.3095748acmotherconferencesArticle/Chapter ViewAbstractPublication PagescbmiConference Proceedingsconference-collections
research-article

Semi-automatic Video Assessment System

Published: 19 June 2017 Publication History

Abstract

This paper describes a system for semi-automatic quality assessment of user generated content (UGC) from large events. It uses image and video processing techniques1 combined with a computational quality model that takes in account aesthetics and how human visual perception and attention mechanisms discriminate visual interest. We describe the approach and show that the developed system allows to sort and filter a large stream of UGC in an efficient and timely manner.

References

[1]
R. Datta, D. Joshi, Jia Li and James Z. Wang. 2006. Studying Aesthetics in Photographic Images Using a Computational Approach. In Lecture Notes in Computer Science, vol. 3953, Proceedings of the European Conference on Computer Vision, Part III, pp. 288--301, Graz, Austria.
[2]
Kuo-Yen Lo, K. Liu and C. Chen. 2012. Assessment of photo aesthetics with efficiency. International Conference on Pattern Recognition. Tsukuba.
[3]
Shehroz S. Khan, D. Vogel. 2012. Evaluating visual aesthetics in photographic portraiture. CAe '12 Proceedings of the Eighth Annual Symposium on Computational Aesthetics in Graphics, Visualization, and Imaging, (pp. 55--62). Annecy, France.
[4]
Yun Zhai and M. Sha. 2006. Visual attention detection in video sequences using spatiotemporal cues. MM '06 Proceedings of the 14th ACM international conference on Multimedia, Pages 815--824, Santa Barbara, CA, USA.
[5]
Z. Huang, P. P. K. Chan, Wing W. Y. Ng, and D. S. Yeung. 2010. Content-based image retrieval using color moment and Gabor texture feature. International Conference on Machine Learning and Cybernetics (ICMLC), Qingdao, China.
[6]
Yiwen Luon and Xiaoou Tang. 2008. Photo and Video Quality Evaluation: Focusing on the Subject. ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III Pages 386--399, Marseille, France.
[7]
A. K. Moorthy. 2010. Towards Computational Models of the Visual Aesthetic Appeal of Consumer Videos. In Lecture Notes in Computer Science, European Conference on Computer Vision -- ECCV 2010, vol. 6315, pages 1--14, Greece.
[8]
C. Tzelepis, E. Mavridaki, V. Mezaris and I. Patras. 2016. Video aesthetic quality assessment using kernel Support Vector Machine with isotropic Gaussian sample uncertainty (KSVM-IGSU). In 2016 IEEE, International Conference on Image Processing (ICIP), Phoenix, AZ, USA.
[9]
Y. Jiang, Y. Wang, R. Feng, X. Xue, Y. Zheng and H. Yang. 2013. Understanding and predicting interestingness of videos. In AAAI'13 Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence, pages 1113--1119, Washington, USA.
[10]
R. Datta, Jia. Li and J. Z. Wang. 2008. Algorithmic inferencing of aesthetics and emotion in natural images: An exposition. In 15th IEEE International Conference on Image Processing, ICIP 2008, San Diego, CA, USA.
[11]
Project Cognitus. Accessed June 2017, at http://cognitus-h2020.eu

Cited By

View all
  • (2018)Ranking News-Quality MultimediaProceedings of the 2018 ACM on International Conference on Multimedia Retrieval10.1145/3206025.3206053(10-18)Online publication date: 5-Jun-2018

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences
CBMI '17: Proceedings of the 15th International Workshop on Content-Based Multimedia Indexing
June 2017
237 pages
ISBN:9781450353335
DOI:10.1145/3095713
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]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 June 2017

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. UGC
  2. aesthetics
  3. interestingness
  4. large events
  5. model of attention and perception
  6. video quality assessment

Qualifiers

  • Research-article
  • Research
  • Refereed limited

Conference

CBMI '17

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)1
  • Downloads (Last 6 weeks)0
Reflects downloads up to 07 Jan 2025

Other Metrics

Citations

Cited By

View all
  • (2018)Ranking News-Quality MultimediaProceedings of the 2018 ACM on International Conference on Multimedia Retrieval10.1145/3206025.3206053(10-18)Online publication date: 5-Jun-2018

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media

  NODES
Association 2
INTERN 14
Note 3
Project 1
USERS 1