Omni-directional camera networks and data fusion for vehicle tracking in an indoor parking lot

Jung Ming Wang*, Ching Ting Tsai, Shen Cherng, Sei Wang Chen

*Corresponding author for this work

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

4 Citations (Scopus)

Abstract

A fixed single camera is not sufficient for monitoring a wide area. More cameras can be used, but a problem with integrating all of them will arise. In this paper, a monitoring system to detect and track moving objects in an indoor environment using multiple omni-directional cameras is proposed. Objects captured from different cameras can be integrated automatically, and we can add more cameras to enlarge the monitoring range without changing the system architecture. Such a system is currently being applied to a model of a parking lot for detecting the paths of vehicles.

Original languageEnglish
Title of host publicationProceedings - IEEE International Conference on Video and Signal Based Surveillance 2006, AVSS 2006
PublisherIEEE Computer Society
Pages45
Number of pages1
ISBN (Print)0769526888, 9780769526881
DOIs
Publication statusPublished - 2006
EventIEEE International Conference on Video and Signal Based Surveillance 2006, AVSS 2006 - Sydney, NSW, Australia
Duration: 2006 Nov 222006 Nov 24

Publication series

NameProceedings - IEEE International Conference on Video and Signal Based Surveillance 2006, AVSS 2006

Conference

ConferenceIEEE International Conference on Video and Signal Based Surveillance 2006, AVSS 2006
Country/TerritoryAustralia
CitySydney, NSW
Period2006/11/222006/11/24

Keywords

  • Homography matrix
  • Hyperbolic mirror
  • Object tracking
  • Omni-directional camera
  • Permutation matrix
  • Surveillance system

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Electrical and Electronic Engineering

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