Application of a neural architecture to extract motion from image sequences

D. E. Swanson; Steven K. Rogers; Dennis W. Ruck

doi:10.1117/12.152565

2 September 1993 Application of a neural architecture to extract motion from image sequences

D. E. Swanson, Steven K. Rogers, Dennis W. Ruck

Proceedings Volume 1965, Applications of Artificial Neural Networks IV; (1993) https://doi.org/10.1117/12.152565
Event: Optical Engineering and Photonics in Aerospace Sensing, 1993, Orlando, FL, United States

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.

Citation Download Citation

D. E. Swanson, Steven K. Rogers, and Dennis W. Ruck "Application of a neural architecture to extract motion from image sequences", Proc. SPIE 1965, Applications of Artificial Neural Networks IV, (2 September 1993); https://doi.org/10.1117/12.152565

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