Proceedings ArticleDOI
Distributed framework for composite event recognition in a calibrated pan-tilt camera network
Ayesha Choudhary,Santanu Chaudhury,Subhashis Banerjee +2 more
- pp 140-147
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TLDR
A novel probabilistic Latent Semantic Analysis based algorithm for pair-wise interaction recognition is proposed and presented as an application of the distributed composite event recognition framework, where the events are interactions between pairs of objects.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.read more
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References
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Book
Fundamentals of speech recognition
TL;DR: This book presents a meta-modelling framework for speech recognition that automates the very labor-intensive and therefore time-heavy and therefore expensive and expensive process of manually modeling speech.
Proceedings Article
Probabilistic latent semantic analysis
TL;DR: This work proposes a widely applicable generalization of maximum likelihood model fitting by tempered EM, based on a mixture decomposition derived from a latent class model which results in a more principled approach which has a solid foundation in statistics.
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Probabilistic Latent Semantic Analysis
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Algorithms for cooperative multisensor surveillance
TL;DR: This paper presents an overview of the issues and algorithms involved in creating this semiautonomous, multicamera surveillance system and its potential to improve the situational awareness of security providers and decision makers.
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Multi camera image tracking
TL;DR: This paper presents a method for multi-camera image tracking in the context of image surveillance that exploits multiple camera views to resolve object occlusion and uses the Linear Kalman Filter, which is less cumbersome to implement than the Extended Kalman filter.