DocumentCode
2100481
Title
Flexible Architecture for Three Classes of Optical Flow Extraction Algorithms
Author
Barren-Zambrano, J.H. ; Torres-Huitzil, Cesar ; Cerda, Mauricio
Author_Institution
Comput. Sci. Dept., INAOE, Tonantzintla
fYear
2008
fDate
3-5 Dec. 2008
Firstpage
13
Lastpage
18
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 witch allow to compute the optical flow at a rate of 50 frames per second with 200times200 gray level images with low resource utilization.
Keywords
estimation theory; field programmable gate arrays; image sequences; motion estimation; dynamic scene analysis; field programmable gate array; flexible architecture; high speed motion estimation; motion scene analysis; optical flow estimation algorithms; optical flow extraction algorithms; parallel hardware architecture; visual perceptual; Computer architecture; Field programmable gate arrays; High speed optical techniques; Image analysis; Image motion analysis; Motion analysis; Navigation; Optical arrays; Optical computing; Visual perception;
fLanguage
English
Publisher
ieee
Conference_Titel
Reconfigurable Computing and FPGAs, 2008. ReConFig '08. International Conference on
Conference_Location
Cancun
Print_ISBN
978-1-4244-3748-1
Electronic_ISBN
978-0-7695-3474-9
Type
conf
DOI
10.1109/ReConFig.2008.61
Filename
4731763
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