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Flexible Architecture for Three Classes of Optical Flow Extraction Algorithms

Hugo Barron-Zambrano 1 César Torres-Huitzil 2 Mauricio Cerda 3
1 Coordinación de Ciencias Computacionales [INAOE]
2 Polytechnic University of Victoria
3 CORTEX - Neuromimetic intelligence
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : Recent findings have shown that several visual perceptual tasks such as 3D navigation and visual attention could use optical flow as a key step in their complex computing models and mechanisms for visual perception of motion and dynamic scene analysis. We have been performing experimental studies to gain understanding of the general principles in the optical flow computation under different approaches so as to establish efficient implementation techniques of embedded systems able to perform high speed motion estimation. Based on these studies, a custom parallel hardware architecture for three classes of optical flow estimation algorithms has been proposed and mapped into a digital implementation. A flexible Field Programmable Gate Array (FPGA) implementation is presented wich allow to compute the optical flow at a rate of 50 200x200 grey level images with low resource utilizatio
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https://hal.inria.fr/inria-00331663
Contributor : Mauricio Cerda <>
Submitted on : Friday, October 17, 2008 - 11:38:45 AM
Last modification on : Friday, February 26, 2021 - 3:28:03 PM

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CNRS | INRIA | LORIA | UNIV-LORRAINE

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Hugo Barron-Zambrano, César Torres-Huitzil, Mauricio Cerda. Flexible Architecture for Three Classes of Optical Flow Extraction Algorithms. Reconfigurable Computing and FPGAs, International Conference on, Dec 2008, Cancun, Mexico. pp.13-18, ⟨10.1109/ReConFig.2008.61⟩. ⟨inria-00331663⟩

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