Information Fusion Using Particles Intersection

Or Tslil, Avishy Carmi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

A technique is presented for combining arbitrary empirical probability density estimates whose interdependencies are unspecified. The underlying estimates may be, for example, the particle approximations of a pair of particle filters. In this respect, our approach provides a way to obtain a new particle approximation, which is better in a precise information-theoretic sense than that of any of the particle filters alone. The viability of the proposed approach is demonstrated in a multiple object tracking scenario.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4269-4273
Number of pages5
ISBN (Print)9781538646588
DOIs
StatePublished - 10 Sep 2018
Event2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Calgary, Canada
Duration: 15 Apr 201820 Apr 2018

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2018-April
ISSN (Print)1520-6149

Conference

Conference2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018
Country/TerritoryCanada
CityCalgary
Period15/04/1820/04/18

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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