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
https://doi.org/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.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
International Conference on Communication and Signal Processing 2016 (ICCASP 2016)
Part of series
Advances in Intelligent Systems Research
Publication Date
December 2016
ISBN
978-94-6252-305-0
DOI
https://doi.org/10.2991/iccasp-16.2017.68How 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  - 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  - International Conference on Communication and Signal Processing 2016 (ICCASP 2016)
PB  - Atlantis Press
UR  - https://doi.org/10.2991/iccasp-16.2017.68
DO  - https://doi.org/10.2991/iccasp-16.2017.68
ID  - Bansod2016/12
ER  -