Multiple target tracking with constrained motion using particle filtering methods

I. Kyriakides, D. Morrell, A. Papandreou-Suppappola

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In this paper, we propose the constrained motion proposal (COMP) algorithm that incorporates target kinematic constraint information into a particle filter to track multiple targets. We represent deterministic or stochastic constraints on target motion as a likelihood function that is incorporated into the particle filter proposal density. Using Monte Carlo simulations, we demonstrate that this approach improves tracking performance while reducing computational cost relative to the independent partition particle filter with and without a constraint likelihood function.

Original languageEnglish
Title of host publicationIEEE CAMSAP 2005 - First International Workshop on Computational Advances in Multi-Sensor Adaptive Processing
Pages85-88
Number of pages4
Volume2005
DOIs
Publication statusPublished - 2005
EventIEEE CAMSAP 2005 - First International Workshop on Computational Advances in Multi-Sensor Adaptive Processing - Puerto Vallarta, Mexico
Duration: 13 Dec 200515 Dec 2005

Other

OtherIEEE CAMSAP 2005 - First International Workshop on Computational Advances in Multi-Sensor Adaptive Processing
CountryMexico
CityPuerto Vallarta
Period13/12/0515/12/05

Fingerprint Dive into the research topics of 'Multiple target tracking with constrained motion using particle filtering methods'. Together they form a unique fingerprint.

  • Cite this

    Kyriakides, I., Morrell, D., & Papandreou-Suppappola, A. (2005). Multiple target tracking with constrained motion using particle filtering methods. In IEEE CAMSAP 2005 - First International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (Vol. 2005, pp. 85-88). [1574190] https://doi.org/10.1109/CAMAP.2005.1574190