FPGA-based Speeded Up Robust Features
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F10%3A00167810" target="_blank" >RIV/68407700:21230/10:00167810 - isvavai.cz</a>
Výsledek na webu
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DOI - Digital Object Identifier
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Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
FPGA-based Speeded Up Robust Features
Popis výsledku v původním jazyce
This software implements Speeded Up Robust Features (SURF) on a Field Programmable Gate Array (FPGA). The SURF algorithm extracts salient points from image and computes descriptors of their surroundings that are invariant to scale, rotation and illumination changes. The interest point detection and feature descriptor extraction algorithm is often used as the first stage in autonomous robot navigation, object recognition and tracking etc. However, detection and extraction are computationally demanding and therefore can't be used in systems with limited computational power. We took advantage of algorithm's natural parallelism and implemented it's most demanding parts in FPGA logic. Several modifications of the original algorithm have been made to increase it's suitability for FPGA implementation. Experiments show, that the FPGA implementation is comparable in terms of precision, speed and repeatability, but outperforms the CPU and GPU implementation in terms of power consumption.
Název v anglickém jazyce
FPGA-based Speeded Up Robust Features
Popis výsledku anglicky
This software implements Speeded Up Robust Features (SURF) on a Field Programmable Gate Array (FPGA). The SURF algorithm extracts salient points from image and computes descriptors of their surroundings that are invariant to scale, rotation and illumination changes. The interest point detection and feature descriptor extraction algorithm is often used as the first stage in autonomous robot navigation, object recognition and tracking etc. However, detection and extraction are computationally demanding and therefore can't be used in systems with limited computational power. We took advantage of algorithm's natural parallelism and implemented it's most demanding parts in FPGA logic. Several modifications of the original algorithm have been made to increase it's suitability for FPGA implementation. Experiments show, that the FPGA implementation is comparable in terms of precision, speed and repeatability, but outperforms the CPU and GPU implementation in terms of power consumption.
Klasifikace
Druh
R - Software
CEP obor
JC - Počítačový hardware a software
OECD FORD obor
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Návaznosti výsledku
Projekt
<a href="/cs/project/2C06005" target="_blank" >2C06005: Systém pro robotickou tele-výuku</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)<br>R - Projekt Ramcoveho programu EK<br>V - Vyzkumna aktivita podporovana z jinych verejnych zdroju
Ostatní
Rok uplatnění
2010
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Interní identifikační kód produktu
FPGA-SURF
Technické parametry
Binární kód jazyka HDL "netlist"
Ekonomické parametry
nejsou stanoveny
IČO vlastníka výsledku
68407700
Název vlastníka
ČVUT FEL, Katedra kybernetiky