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Proceedings Paper

Application of a neural architecture to extract motion from image sequences
Author(s): D. E. Swanson; Steven K. Rogers; Dennis W. Ruck
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Paper Abstract

Investigation of two neural architectures is performed in two dimensions using both synthetic and real imagery. Our model follows the work performed by H. Ogmen and S. Gagne in 1990 on the fly's visual system. We extended their model to a two-dimensional architecture and also developed a new model by adding long-term memory at the input--adaptive model. Our investigation compares the response of the adaptive model against the original Ogmen and Gagne's cell-activity model. The output of both models were further processed using casual and noncausal moving average filters to help remove tonic image elements and identify direction of motion. Our simulations show that the adaptive model can be used to segment motion from sequences of imagery.

Paper Details

Date Published: 2 September 1993
PDF: 11 pages
Proc. SPIE 1965, Applications of Artificial Neural Networks IV, (2 September 1993); doi: 10.1117/12.152565
Show Author Affiliations
D. E. Swanson, Air Force Institute of Technology (United States)
Steven K. Rogers, Air Force Institute of Technology (United States)
Dennis W. Ruck, Air Force Institute of Technology (United States)

Published in SPIE Proceedings Vol. 1965:
Applications of Artificial Neural Networks IV
Steven K. Rogers, Editor(s)

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