Complex event recognition with uncertainty reasoning

Xueqin Liu; Kathy Clawson; Hui Wang; Bryan Scotney; Jun Liu

doi:10.1109/ICMLC.2013.6890893

Complex event recognition with uncertainty reasoning

Xueqin Liu, Kathy Clawson, Hui Wang, Bryan Scotney, Jun Liu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Citations (Scopus)

Abstract

The goal of complex event recognition considered in this paper is the automatic detection of complex high-level events in videos. This is a difficult task, especially when videos are captured under unconstrained conditions, with poor lighting, heavy background clutter and occlusion. In this paper, we propose a hierarchical knowledge-based framework for complex event recognition. The video event knowledge represents an arbitrary complex spatio-temporal event as a hierarchical composition of simpler events in a natural way. Uncertainty reasoning procedures are applied to interpret low level event descriptions according to the video knowledge base in order to recognize high level scenarios.

Original language	English
Title of host publication	Proceedings - International Conference on Machine Learning and Cybernetics
Publisher	IEEE Computer Society
Pages	1823-1828
Number of pages	6
ISBN (Electronic)	9781479902576
DOIs	https://doi.org/10.1109/ICMLC.2013.6890893
Publication status	Published (in print/issue) - 2013
Event	12th International Conference on Machine Learning and Cybernetics, ICMLC 2013 - Tianjin, China Duration: 14 Jul 2013 → 17 Jul 2013

Publication series

Name	Proceedings - International Conference on Machine Learning and Cybernetics
Volume	4
ISSN (Print)	2160-133X
ISSN (Electronic)	2160-1348

Conference

Conference	12th International Conference on Machine Learning and Cybernetics, ICMLC 2013
Country/Territory	China
City	Tianjin
Period	14/07/13 → 17/07/13

Bibliographical note

Publisher Copyright:
© 2013 IEEE.

Keywords

Complex event recognition
Hierarchical approach
Knowledge base
Uncertainty reasoning
Video pattern recognition

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/ICMLC.2013.6890893

Cite this

Liu, X., Clawson, K., Wang, H., Scotney, B., & Liu, J. (2013). Complex event recognition with uncertainty reasoning. In Proceedings - International Conference on Machine Learning and Cybernetics (pp. 1823-1828). Article 6890893 (Proceedings - International Conference on Machine Learning and Cybernetics; Vol. 4). IEEE Computer Society. https://doi.org/10.1109/ICMLC.2013.6890893

@inproceedings{a3d2c8fbded74483a4ea0e1cdc3990e5,

title = "Complex event recognition with uncertainty reasoning",

abstract = "The goal of complex event recognition considered in this paper is the automatic detection of complex high-level events in videos. This is a difficult task, especially when videos are captured under unconstrained conditions, with poor lighting, heavy background clutter and occlusion. In this paper, we propose a hierarchical knowledge-based framework for complex event recognition. The video event knowledge represents an arbitrary complex spatio-temporal event as a hierarchical composition of simpler events in a natural way. Uncertainty reasoning procedures are applied to interpret low level event descriptions according to the video knowledge base in order to recognize high level scenarios.",

keywords = "Complex event recognition, Hierarchical approach, Knowledge base, Uncertainty reasoning, Video pattern recognition",

author = "Xueqin Liu and Kathy Clawson and Hui Wang and Bryan Scotney and Jun Liu",

note = "Publisher Copyright: {\textcopyright} 2013 IEEE.; 12th International Conference on Machine Learning and Cybernetics, ICMLC 2013 ; Conference date: 14-07-2013 Through 17-07-2013",

year = "2013",

doi = "10.1109/ICMLC.2013.6890893",

language = "English",

series = "Proceedings - International Conference on Machine Learning and Cybernetics",

publisher = "IEEE Computer Society",

pages = "1823--1828",

booktitle = "Proceedings - International Conference on Machine Learning and Cybernetics",

address = "United States",

}

Liu, X, Clawson, K, Wang, H, Scotney, B & Liu, J 2013, Complex event recognition with uncertainty reasoning. in Proceedings - International Conference on Machine Learning and Cybernetics., 6890893, Proceedings - International Conference on Machine Learning and Cybernetics, vol. 4, IEEE Computer Society, pp. 1823-1828, 12th International Conference on Machine Learning and Cybernetics, ICMLC 2013, Tianjin, China, 14/07/13. https://doi.org/10.1109/ICMLC.2013.6890893

Complex event recognition with uncertainty reasoning. / Liu, Xueqin; Clawson, Kathy; Wang, Hui et al.
Proceedings - International Conference on Machine Learning and Cybernetics. IEEE Computer Society, 2013. p. 1823-1828 6890893 (Proceedings - International Conference on Machine Learning and Cybernetics; Vol. 4).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Complex event recognition with uncertainty reasoning

AU - Liu, Xueqin

AU - Clawson, Kathy

AU - Wang, Hui

AU - Scotney, Bryan

AU - Liu, Jun

PY - 2013

Y1 - 2013

N2 - The goal of complex event recognition considered in this paper is the automatic detection of complex high-level events in videos. This is a difficult task, especially when videos are captured under unconstrained conditions, with poor lighting, heavy background clutter and occlusion. In this paper, we propose a hierarchical knowledge-based framework for complex event recognition. The video event knowledge represents an arbitrary complex spatio-temporal event as a hierarchical composition of simpler events in a natural way. Uncertainty reasoning procedures are applied to interpret low level event descriptions according to the video knowledge base in order to recognize high level scenarios.

AB - The goal of complex event recognition considered in this paper is the automatic detection of complex high-level events in videos. This is a difficult task, especially when videos are captured under unconstrained conditions, with poor lighting, heavy background clutter and occlusion. In this paper, we propose a hierarchical knowledge-based framework for complex event recognition. The video event knowledge represents an arbitrary complex spatio-temporal event as a hierarchical composition of simpler events in a natural way. Uncertainty reasoning procedures are applied to interpret low level event descriptions according to the video knowledge base in order to recognize high level scenarios.

KW - Complex event recognition

KW - Hierarchical approach

KW - Knowledge base

KW - Uncertainty reasoning

KW - Video pattern recognition

UR - https://www.scopus.com/pages/publications/84907276323

U2 - 10.1109/ICMLC.2013.6890893

DO - 10.1109/ICMLC.2013.6890893

M3 - Conference contribution

AN - SCOPUS:84907276323

T3 - Proceedings - International Conference on Machine Learning and Cybernetics

SP - 1823

EP - 1828

BT - Proceedings - International Conference on Machine Learning and Cybernetics

PB - IEEE Computer Society

T2 - 12th International Conference on Machine Learning and Cybernetics, ICMLC 2013

Y2 - 14 July 2013 through 17 July 2013

ER -

Complex event recognition with uncertainty reasoning

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

Access to Document

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