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Proceedings Paper

Neural Network For Optical Flow Estimation
Author(s): Roger Samy
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Paper Abstract

A method for optical flow estimation from an image sequence using a neural network is presented. Under hypothesis based on local rigidity, translational motion and smoothness constraints, a neural network is designed to estimate the optical flow. Experimental results using real world I.R. images are presented to demonstrate the efficiency of this method compared to Horn and Schunck algorithm.

Paper Details

Date Published: 1 March 1990
PDF: 8 pages
Proc. SPIE 1192, Intelligent Robots and Computer Vision VIII: Algorithms and Techniques, (1 March 1990); doi: 10.1117/12.969757
Show Author Affiliations
Roger Samy, Societe Anonyme des Telecommunications (France)

Published in SPIE Proceedings Vol. 1192:
Intelligent Robots and Computer Vision VIII: Algorithms and Techniques
David P. Casasent, Editor(s)

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