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Activity Number:
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308
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Type:
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Topic Contributed
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Date/Time:
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Tuesday, August 4, 2009 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Bayesian Statistical Science
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| Abstract - #304170 |
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Title:
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Variational Mean Field Approach to Efficient Multitarget Tracking
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Author(s):
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Ernest Fokoue*+
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Companies:
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Kettering University
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Address:
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1700 West Third Avenue, Flint, MI, 48504,
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Keywords:
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Sequential Monte Carlo ; Multitarget Tracking ; Efficient ; Approximate ; Posterior ; Mean Field
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Abstract:
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We present various aspects of a variational mean field alternative to MCMC-based particle algorithms for multi-target tracking. Our proposed method is motivated by both clarity and efficiency with an emphasis on the derivation of updating schemes that are fast. In the spirit of traditional variational mean field inference, our intractable posteriors of interest are approximated by more tractable counterparts with the immediate advantage being the rapid generation of the desired proposals. Our work is compared to Francois Septier's MCMC-based particle algorithm from which most of the building blocks of our methods are borrowed.
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