Novel Anomalous Event Detection based on Human-object Interactions

Rensso Mora Colque, Carlos Caetano, Victor C. de Melo, Guillermo Camara Chavez, William Robson Schwartz

Abstract

This study proposes a novel approach to anomalous event detection that collects information from a specific context and is flexible enough to work in different scenes (i.e., the camera does need to be at the same location or in the same scene for the learning and test stages of anomaly event detection), making our approach able to learn normal patterns (i.e., patterns that do not entail an anomaly) from one scene and be employed in another as long as it is within the same context. For instance, our approach can learn the normal behavior for a context such the office environment by \emph{watching} a particular office, and then it can monitor the behavior in another office, without being constrained to aspects such as camera location, optical flow or trajectories, as required by the current works. Our paradigm shift anomalous event detection approach exploits human-object interactions to learn normal behavior patterns from a specific context. Such patterns are used afterwards to detect anomalous events in a different scene. The proof of concept shown in the experimental results demonstrate the viability of two strategies that exploit this novel paradigm to perform anomaly detection.

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Paper Citation


in Harvard Style

Mora Colque R., Caetano C., de Melo V., Camara Chavez G. and Schwartz W. (2018). Novel Anomalous Event Detection based on Human-object Interactions.In Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, ISBN 978-989-758-290-5, pages 293-300. DOI: 10.5220/0006615202930300


in Bibtex Style

@conference{visapp18,
author={Rensso Mora Colque and Carlos Caetano and Victor C. de Melo and Guillermo Camara Chavez and William Robson Schwartz},
title={Novel Anomalous Event Detection based on Human-object Interactions},
booktitle={Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,},
year={2018},
pages={293-300},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006615202930300},
isbn={978-989-758-290-5},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,
TI - Novel Anomalous Event Detection based on Human-object Interactions
SN - 978-989-758-290-5
AU - Mora Colque R.
AU - Caetano C.
AU - de Melo V.
AU - Camara Chavez G.
AU - Schwartz W.
PY - 2018
SP - 293
EP - 300
DO - 10.5220/0006615202930300