Evaluation of a posteriori probabilities of multi-frame data association hypotheses

Shozo Mori; Chee Chong

doi:10.1117/12.734822

21 September 2007 Evaluation of a posteriori probabilities of multi-frame data association hypotheses

Shozo Mori, Chee Chong

Proceedings Volume 6699, Signal and Data Processing of Small Targets 2007; 66990L (2007) https://doi.org/10.1117/12.734822
Event: Optical Engineering + Applications, 2007, San Diego, California, United States

Abstract

This paper discusses the problem of numerically evaluating multi-frame, data-association hypotheses in multiple-target tracking in terms of their a posteriori probabilities. We describe two approaches to the problem: (1) an approach based on K-best multi-frame data association hypothesis selection algorithms, and (2) a more direct approach to calculating a posteriori probabilities through Markov-chain-Monte-Carlo (MCMC) or sequential Monte Carlo (SMC) methods. This paper defines algorithms based on those two approaches and compares their performance, and it discusses their relative effectiveness, using simple numerical examples.

Citation Download Citation

Shozo Mori and Chee Chong "Evaluation of a posteriori probabilities of multi-frame data association hypotheses", Proc. SPIE 6699, Signal and Data Processing of Small Targets 2007, 66990L (21 September 2007); https://doi.org/10.1117/12.734822

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