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2013 IEEE International Conference on Multimedia and Expo Workshops (ICMEW) (2013)
San Jose, CA, USA
July 15, 2013 to July 19, 2013
ISBN: 978-1-4799-1604-7
pp: 1-6
Itir Onal , Department of Computer Engineering, Middle East Technical University, Ankara, Turkey
Karani Kardas , Department of Computer Engineering, Middle East Technical University, Ankara, Turkey
Yousef Rezaeitabar , Department of Electrical and Electronics Engineering, Middle East Technical University, Ankara, Turkey
Ulya Bayram , Department of Electrical and Electronics Engineering, Middle East Technical University, Ankara, Turkey
Murat Bal , Department of Computer Engineering, Middle East Technical University, Ankara, Turkey
Ilkay Ulusoy , Department of Electrical and Electronics Engineering, Middle East Technical University, Ankara, Turkey
Nihan Kesim Cicekli , Department of Computer Engineering, Middle East Technical University, Ankara, Turkey
ABSTRACT
This paper presents a framework for detecting complex events in surveillance videos. Moving objects in the foreground are detected in the object detection component of the system. Whether these foregrounds are human or not is decided in the object recognition component. Then each detected object is tracked and labeled in the object tracking component, in which true labeling of objects in the occlusion situation is also provided. The extracted information is fed to the event detection component. Rule based event models are created and trained using Markov Logic Networks (MLNs) so that each rule is given a weight. Events are inferred using MLNs where the assigned weights are used to determine whether an event occurs or not. The proposed system can be applied to detect many complex events simultaneously. In this paper, detection of left object event is discussed and evaluated using PETS-2006, CANTATA and our dataset.
INDEX TERMS
Tracking, Event Detection, Markov Logic Networks, Video Surveillance, Foreground Detection, Human Recognition
CITATION

I. Onal et al., "A framework for detecting complex events in surveillance videos," 2013 IEEE International Conference on Multimedia and Expo Workshops (ICMEW), San Jose, CA, USA, 2013, pp. 1-6.
doi:10.1109/ICMEW.2013.6618411
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