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Proceedings Paper

Pyramidal Markov random field (MRF) models for optical flow estimation applied to target detection
Author(s): Roger A. Samy; Daniel Duclos
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Paper Abstract

In air-to-ground applications, the detection of target is a difficult problem due to complex background where classical detection algorithms generate a large amount of false alarms. This paper addresses the detection of moving target based on motion compensated sequences. In the presence of noisy image acquisition and motion discontinuities, the estimation of optical flow is reformulated in robust estimation framework. The motion estimation is based on robust optical flow algorithm developed in the pyramidal Markov Random Model framework. We present the results of this detection algorithm on real-world airborne I.R. image sequence.

Paper Details

Date Published: 22 June 1994
PDF: 6 pages
Proc. SPIE 2233, Sensor Fusion and Aerospace Applications II, (22 June 1994); doi: 10.1117/12.179033
Show Author Affiliations
Roger A. Samy, Societe Anonyme des Telecommunication (France)
Daniel Duclos, Societe Anonyme des Telecommunication (France)

Published in SPIE Proceedings Vol. 2233:
Sensor Fusion and Aerospace Applications II
Nagaraj Nandhakumar, Editor(s)

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