Proceedings of the International Conference on Communication and Signal Processing 2016 (ICCASP 2016)

Detection and Localization of Anomalies from Videos based on Optical flow Magnitude and Direction

Authors
S. Bansod, A. Nandedkar
Corresponding Author
S. Bansod
Available Online December 2016.
DOI
10.2991/iccasp-16.2017.68How to use a DOI?
Keywords
Anomalies, optical flow, directional motion.
Abstract

Anomalies in video scenes means unexpected or unusual activity which is usually not frequently observed. Such activities hence are rare and require sudden attention so that it can be detected as early as possible. There is a need to automatically identify and locate where such anomaly is present. Optical flow magnitude and di-rection based method is an automated system built on motion, position and statistical features of moving ob-jects present in video. Moving objects are identified by means of optical flow and are represented using bound-ing box. The normal behaviors is learned beforehand for different objects. A generalization of normal behavior is captured by clustering different directional motions in the scene. Anomalous behavior of objects are detected and localized using motion and positions differing from normal behavior. The performance of proposed meth-od is compared with existing methods by using standard benchmark datasets available online such as UCSD and UMN.

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/).

Download article (PDF)

Volume Title
Proceedings of the International Conference on Communication and Signal Processing 2016 (ICCASP 2016)
Series
Advances in Intelligent Systems Research
Publication Date
December 2016
ISBN
10.2991/iccasp-16.2017.68
ISSN
1951-6851
DOI
10.2991/iccasp-16.2017.68How 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  - S. Bansod
AU  - A. Nandedkar
PY  - 2016/12
DA  - 2016/12
TI  - Detection and Localization of Anomalies from Videos based on Optical flow Magnitude and Direction
BT  - Proceedings of the International Conference on Communication and Signal Processing 2016 (ICCASP 2016)
PB  - Atlantis Press
SP  - 454
EP  - 462
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccasp-16.2017.68
DO  - 10.2991/iccasp-16.2017.68
ID  - Bansod2016/12
ER  -