Gaussian Approximation for Tracking Occluding and Interacting Targets

Carlos Medrano, Jesús Martínez, Raúl Igual, José Elías Herrero, Carlos Orrite

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

In this paper, we show how interacting and occluding targets can be tackled successfully within a Gaussian approximation. For that purpose, we develop a general expansion of the mean and covariance of the posterior and we consider a first order approximation of it. The proposed method differs from EKF in that neither a non-linear dynamical model nor a non-linear measurement vector to state relation have to be defined, so it works with any kind of interaction potential and likelihood. The approach has been tested on three sequences (10400, 2500, and 400 frames each one). The results show that our approach helps to reduce the number of failures without increasing too much the computation time with respect to methods that do not take into account target interactions.
Original languageEnglish
Pages (from-to)241-253
Number of pages13
JournalJournal of Mathematical Imaging and Vision
Volume36
Issue number3
DOIs
Publication statusPublished - Mar 2010

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Modelling and Simulation
  • Geometry and Topology
  • Applied Mathematics
  • Statistics and Probability
  • Condensed Matter Physics

Fingerprint

Dive into the research topics of 'Gaussian Approximation for Tracking Occluding and Interacting Targets'. Together they form a unique fingerprint.

Cite this