Robust fusion of uncertain information

  • Haifeng Chen
  • , Peter Meer

Research output: Contribution to journalArticlepeer-review

40 Scopus citations

Abstract

A technique is presented to combine n data points, each available with point-dependent uncertainty, when only a subset of these points come from N ≪ n sources, where N is unknown. We detect the significant modes of the underlying multivariate probability distribution using a generalization of the nonparametric mean shift procedure. The number of detected modes automatically defines N, while the belonging of a point to the basin of attraction of a mode provides the fusion rule. The robust data fusion algorithm was successfully applied to two computer vision problems: estimating the multiple affine transformations, and range image segmentation.

Original languageEnglish (US)
Pages (from-to)578-586
Number of pages9
JournalIEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Volume35
Issue number3
DOIs
StatePublished - Jun 2005

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering

Keywords

  • Computer vision
  • Information fusion
  • Mean shift
  • Robust analysis

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