Quality-based fusion of multiple video sensors for video surveillance

Lauro Snidaro, Ruixin Niu, Gian Luca Foresti, Pramond K. Varshney

Research output: Contribution to journalArticle

26 Scopus citations

Abstract

In this correspondence, we address the problem of fusing data for object tracking for video surveillance. The fusion process is dynamically regulated to take into account the performance of the sensors in detecting and tracking the targets. This is performed through a function that adjusts the measurement error covariance associated with the position information of each target according to the quality of its segmentation. In this manner, localization errors due to incorrect segmentation of the blobs are reduced thus improving tracking accuracy. Experimental results on video sequences of outdoor environments show the effectiveness of the proposed approach.

Original languageEnglish (US)
Pages (from-to)1044-1051
Number of pages8
JournalIEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Volume37
Issue number4
DOIs
StatePublished - Aug 1 2007

Keywords

  • Data fusion
  • Object tracking
  • Segmentation quality
  • Video surveillance

ASJC Scopus subject areas

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

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