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Real-Time Multi-Object Tracking using Random Finite Sets

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5 Author(s)
Stephan Reuter ; Institute of Measurement, Control and Microtechnology, Germany ; Benjamin Wilking ; Jurgen Wiest ; Michael Munz
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The multi-object Bayes (MOB) filter uses random finite sets (RFSs) to represent a scene. A drawback of this filter is the computational complexity of the multi-object likelihood function. In this contribution, an approximation of the multi-object likelihood function is presented allowing for real-time implementation on a graphics processing unit using sequential Monte Carlo (SMC) methods. Additionally, a track extraction algorithm using clustering as well as an approach to determine the existence probability of each single object are proposed.

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IEEE Transactions on Aerospace and Electronic Systems  (Volume:49 ,  Issue: 4 )