Artificial Perception Laboratory

ENV #19: Extraction of Features from Remote-Sensed Imagery
for a Search and Rescue Synthetic Vision Database


The development of synthetic vision systems for search and rescue applications allow helicopter pilots to fly under low-visibility conditions. However, the actual databases are generated manually and their accuracy is not known. In order to use this system across Canada, some automated methods are needed to generate complete and accurate topographic databases from multiple sources of remote-sensed data.

This Geoide project is a collaboration of researchers from McGill University, Laval University, York University, University of Waterloo, University of British Columbia and Crestech.

The members of the Artificial Perception Laboratory participating in this project are:

Prof. Frank P. Ferrie
Philippe Simard (Ph.D. student)
Isabelle Bégin (Ph.D. student)


Poster presentation

Simard, P., Bégin, I., Soucy, G., Ferrie, F.P., "A Probabilistic Framework for Automatic Terrestrial Feature Extraction from Remote-Sensed Imagery", Proceedings of the Second Geoide Annual Meeting, Calgary (Alberta), May 2000.
Poster (pdf)

Future projects

  • Online Database Updating by Change Detection
  • Fusion of Remote-Sensed Images from Multiple Sources


    McGill Centre for Intelligent Machines
    Artificial Perception Laboratory
    ENV#19 - Geoide
    ENV #19 - Dr. Rob Reeves (York U.)

    Isabelle Bégin
    Last modified: Mon Apr 23 13:19:52 EDT 2001