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.
Real-Time Multi-Object Tracking using Random Finite Sets
IEEE Transactions on Aerospace and Electronic Systems ; 49 , 4 ; 2666-2678
2013-10-01
2376463 byte
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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