About: FPGA-Based Module for SURF Extraction

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

Attributes	Values
rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
rdfs:seeAlso	http://link.springer.com/article/10.1007%2Fs00138-014-0599-0
Description	We present a complete hardware and software solution of an FPGA-based computer vision embedded module capable of carrying out SURF image features extraction algorithm. Aside from image analysis, the module embeds a Linux distribution that allows to run programs specifically tailored for particular applications. The module is based on a Virtex-5 FXT FPGA which features powerful configurable logic and an embedded PowerPC processor. We describe the module hardware as well as the custom FPGA image processing cores that implement the algorithm's most computationally expensive process, the interest point detection. The module's overall performance is evaluated and compared to CPU and GPU based solutions. Results show that the embedded module achieves comparable disctinctiveness to the SURF software implementation running in a standard CPU while being faster and consuming significantly less power and space. Thus, it allows to use the SURF algorithm in applications with power and spatial constraints, such as autonomous navigation of small mobile robots. We present a complete hardware and software solution of an FPGA-based computer vision embedded module capable of carrying out SURF image features extraction algorithm. Aside from image analysis, the module embeds a Linux distribution that allows to run programs specifically tailored for particular applications. The module is based on a Virtex-5 FXT FPGA which features powerful configurable logic and an embedded PowerPC processor. We describe the module hardware as well as the custom FPGA image processing cores that implement the algorithm's most computationally expensive process, the interest point detection. The module's overall performance is evaluated and compared to CPU and GPU based solutions. Results show that the embedded module achieves comparable disctinctiveness to the SURF software implementation running in a standard CPU while being faster and consuming significantly less power and space. Thus, it allows to use the SURF algorithm in applications with power and spatial constraints, such as autonomous navigation of small mobile robots. (en)
Title	FPGA-Based Module for SURF Extraction FPGA-Based Module for SURF Extraction (en)
skos:prefLabel	FPGA-Based Module for SURF Extraction FPGA-Based Module for SURF Extraction (en)
skos:notation	RIV/68407700:21230/14:00213880!RIV15-MSM-21230___
http://linked.open...avai/riv/aktivita	P
http://linked.open...avai/riv/aktivity	P(7AMB12AR022), P(7E08006)
http://linked.open...iv/cisloPeriodika	3
http://linked.open...vai/riv/dodaniDat	2015
http://linked.open...aciTvurceVysledku	Čížek, Petr Šváb, Jan Přeučil, Libor Krajník, Tomáš
http://linked.open.../riv/druhVysledku	J - Článek v odborném periodiku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	České vysoké učení technické v Praze / Fakulta elektrotechnická
http://linked.open...dnocenehoVysledku	17383
http://linked.open...ai/riv/idVysledku	RIV/68407700:21230/14:00213880
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	SURF; FPGA; Monocular Navigation; Embedded Systems; Feature Extraction (en)
http://linked.open.../riv/klicoveSlovo	Monocular Navigation SURF Feature Extraction FPGA Embedded Systems
http://linked.open...odStatuVydavatele	DE - Spolková republika Německo
http://linked.open...ontrolniKodProRIV	[B8497302FC69]
http://linked.open...i/riv/nazevZdroje	Machine Vision and Applications
http://linked.open...in/vavai/riv/obor	JD
http://linked.open...ichTvurcuVysledku	4 (xsd:int)
http://linked.open...cetTvurcuVysledku	5 (xsd:int)
http://linked.open...vavai/riv/projekt	Cognitive Autonomous Robots II Robotic Evolutionary Self-Programming and Self-Assembling Organisms
http://linked.open...UplatneniVysledku	2014
http://linked.open...v/svazekPeriodika	25
http://linked.open...iv/tvurceVysledku	Krajník, Tomáš Přeučil, Libor Čížek, Petr Šváb, Jan Pedre, S.
http://linked.open...ain/vavai/riv/wos	000333364300017
issn	0932-8092
number of pages	14 (xsd:int)
http://bibframe.org/vocab/doi	10.1007/s00138-014-0599-0
http://localhost/t...ganizacniJednotka	21230

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