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Proceedings Paper

DSP structure to motion computation on reconfigurable hardware
Author(s): Guillermo Botella; Antonio García; Manuel Rodríguez; Uwe Meyer-Baese
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Paper Abstract

Since the world presents a dynamically changing environment, we need synthetic systems that can process and respond to motion. The main contribution of this work is the efficient implementation of a biologically inspired DSP architecture for gradient motion estimation that borrows nature templates as inspiration and makes use of an specific model of human visual motion perception: Multi Channel Gradient Model. This model can be enhanced using psychophysical and bioinspired properties according to biological vision in order to mimic the behavior and the performance of the mammalians. The architecture is designed with an asynchronous pipeline, chaining several signal processing stages. Experimental results and resource consumption are discussed, analyzing the associated customization of the system. This work concludes with several comparisons with the actual contributions and examples for synthetic sequences and real image applications.

Paper Details

Date Published: 19 March 2009
PDF: 10 pages
Proc. SPIE 7343, Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering VII, 73430X (19 March 2009); doi: 10.1117/12.818345
Show Author Affiliations
Guillermo Botella, Univ. Complutense de Madrid (Spain)
Antonio García, Univ. de Granada (Spain)
Manuel Rodríguez, Univ. de Granada (Spain)
Uwe Meyer-Baese, Florida State Univ. (United States)


Published in SPIE Proceedings Vol. 7343:
Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering VII
Harold H. Szu; F. Jack Agee, Editor(s)

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