Change-driven data flow image processing architecture for optical flow computation

Optical flow computation has been extensively used for motion estimation of objects in image sequences. The results obtained by most optical flow techniques are computationally intensive due to the large amount of data involved. A new change-based data flow pipelined architecture has been developed implementing the Horn and Schunk smoothness constraint; pixels of the image sequence that significantly change, fire the execution of the operations related to the image processing algorithm. This strategy reduces the data and, combined with the custom hardware implemented, it achieves a significant optical flow computation speed-up with no loss of accuracy. This paper presents the bases of the change-driven data flow image processing strategy, as well as the implementation of custom hardware developed using an Altera Stratix PCI development board.

Rocío Gómez-FabelaEmail:

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Julio C. Sosa   received the degree in electronic engineering in 1997 from the Instituto Tecnológico de Lázaro Cárdenas, México, the M.Sc. degree in electrical engineering in 2000 from the Centro de Investigacón y de Estudios Avanzadosthen del I.P.N., México and he is candidate to Ph.D. by University of Valencia, Spain. Currently he is associate professor at the Postgrade Department, the Escuela Superior de Cómputo—I.P.N. México. His research interests include hardware architectures, artificial intelligence and microelectronic. Jose A. Boluda   was born in Xàtiva (Spain) in 1969. He graduated in physics (1992) and received his Ph.D. (2000) in physics, both at the University of Valencia. From 1993, he was with the electronics and computer science department of the University of Valencia, Spain, where he collaborated in several projects related to ASIC design and image processing. He has been a visiting researcher with the Department of Electrical Engineering at the University of Virginia, USA and the Department of Applied Informatics at the University of Macedonia, Greece. He is currently Titular Professor in the Department of Informatics at the University of Valencia. His research interests include reconfigurable systems, VHDL hardware design, programmable logic synthesis and sensor design. Fernando Pardo   received the M.S. degree in physics from the University of Valencia, Valencia, Spain in 1991, and the Ph.D. in computer engineering from the University of Valencia, Valencia, Spain in 1997. From 1991 to 1993, he was with the Electronics and Computer Science department of the University of Valencia, Spain, where he collaborated in several research projects. In 1994 he was with the Integrated Laboratory for Advanced Robotics at the University of Genoa, Italy, where he worked on space-variant image processing. In 1994 he joined IMEC (Interuniversitary Micro-Electronics Centre), Belgium, where he worked on projects related to CMOS space-variant image sensors. In 1995 he joined the University of Valencia, Spain, where he is currently Associate Professor and the Head of the Computer Engineering Department. He is currently leading several projects regarding architectures for high-speed image processing and bio-inspired image sensors. Rocío Gómez-Fabela   was born in México City in 1979. She received the Computer Engineering degree in 2001 from Escuela Superior de Cómputo, México. She is currently studying towards the Ph.D. in the Department of Informatics, University of Valencia, Spain. Her current research interests are softcomputing, reconfigurable systems and VHDL hardware design.