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SUMMARY:Multi-Target Bayes Filtering with Random Finite Sets - Paul Peelin
 g
DTSTART:20061215T153000Z
DTEND:20061215T170000Z
UID:TALK5803@talks.cam.ac.uk
CONTACT:Taylan Cemgil
DESCRIPTION:Random finite sets are a natural framework for tracking an unk
 nown number of moving targets. Explicit association between measurements a
 nd targets can be avoided by adopting a point-process formalisim. This lea
 ds to a Bayes multi-target filter with a SMC implementation. Practically t
 his is inefficient for many targets. The Probability Hypothesis Density (P
 HD) approximates the multi-target posterior in the single-target space\, a
 nd is more tractable to compute in an SMC implementation. \n\nI will cover
  the above theory and implementation\, and motivate its application to aut
 omatic polyphonic music transcription\n\nVo B-N.\, Singh S.S.\, and Doucet
  A.\, Sequential Monte Carlo methods for Multi-target Filtering with Rando
 m Finite Sets\, IEEE Aerospace and Electronic Systems\, June 2005 \nhttp:/
 /www-sigproc.eng.cam.ac.uk/%7Esss40/papers/Vo05_smcForMultiTargetFiltering
 WthRandomSets.pdf\n\n
LOCATION:Engineering Department\, Baker Building\, Division F meeting room
 \, 5th floor
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