Cited By
View all- Choudhary AChaudhury S(2016)Video analytics revisitedIET Computer Vision10.1049/iet-cvi.2015.032110:4(237-249)Online publication date: 4-Mar-2016
Distributed framework for composite event recognition in a calibrated pan-tilt camera network
Pages 140 - 147
Abstract
In this paper, we propose a real-time distributed framework for composite event recognition in a calibrated pan-tilt camera network. A composite event comprises of events that occur simultaneously or sequentially at different locations across time. Distributed composite event recognition requires distributed multi-camera multi-object tracking and distributed multi-camera event recognition. We apply belief propagation to reach a consensus on the global identities of the objects in the pan-tilt camera network and to arrive at a consensus on the event recognized by multiple cameras simultaneously observing it. We propose a hidden Markov model based approach for composite event recognition. We also propose a novel probabilistic Latent Semantic Analysis based algorithm for pair-wise interaction recognition and present an application of our distributed composite event recognition framework, where the events are interactions between pairs of objects.
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Index Terms
- Distributed framework for composite event recognition in a calibrated pan-tilt camera network
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Information
Published In
December 2010
533 pages
ISBN:9781450300605
DOI:10.1145/1924559
- General Chairs:
- Rama Chellappa,
- Padmanabhan Anandan,
- Program Chairs:
- A. N. Rajagopalan,
- P. J. Narayanan,
- Philip Torr
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Association for Computing Machinery
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Published: 12 December 2010
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ICVGIP '10
ICVGIP '10: Seventh Indian Conference on Computer Vision, Graphics and Image Processing
December 12 - 15, 2010
Chennai, India
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View all- Choudhary AChaudhury S(2016)Video analytics revisitedIET Computer Vision10.1049/iet-cvi.2015.032110:4(237-249)Online publication date: 4-Mar-2016
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