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Anti-social behavior detection in audio-visual surveillance systems

Kuklyte, Jogile and Kelly, Philip and Ó Conaire, Ciarán and O'Connor, Noel E. and Xu, Li-Qun (2009) Anti-social behavior detection in audio-visual surveillance systems. In: PRAI*HBA - The Workshop on Pattern Recognition and Artificial Intelligence for Human Behaviour Analysis, 9-11 December 2009, Reggio Emilia, Italy.

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In this paper we propose a general purpose framework for detection of unusual events. The proposed system is based on the unsupervised method for unusual scene detection in web{cam images that was introduced in [1]. We extend their algorithm to accommodate data from different modalities and introduce the concept of time-space blocks. In addition, we evaluate early and late fusion techniques for our audio-visual data features. The experimental results on 192 hours of data show that data fusion of audio and video outperforms using a single modality.

Item Type:Conference or Workshop Item (Paper)
Event Type:Workshop
Subjects:Computer Science > Machine learning
Engineering > Signal processing
Computer Science > Algorithms
Computer Science > Image processing
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
Research Initiatives and Centres > CLARITY: The Centre for Sensor Web Technologies
Official URL:
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland, SFI 07/CE/I114, Irish Research Council for Science Engineering and Technology
ID Code:15004
Deposited On:21 Dec 2009 13:31 by Philip Kelly. Last Modified 04 Nov 2016 11:14

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