Pregled bibliografske jedinice broj: 1119096
Comparison between feature-based and phase correlation methods for ROV vision-based speed estimation
Comparison between feature-based and phase correlation methods for ROV vision-based speed estimation // IFAC Proceedings Volumes, Volume 43, Issue 16,
Lecce, Italija: Elsevier, 2010. str. 449-454 doi:10.3182/20100906-3-it-2019.00078 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1119096 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Comparison between feature-based and phase
correlation methods for ROV vision-based speed
estimation
Autori
Ferreira, F. ; Orsenigo, F. ; Veruggio, G. ; Pavlakis, P. ; Caccia, M. ; Bruzzone, G.
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
IFAC Proceedings Volumes, Volume 43, Issue 16,
/ - : Elsevier, 2010, 449-454
Skup
7th IFAC Symposium on Intelligent Autonomous Vehicles
Mjesto i datum
Lecce, Italija, 06.09.2010. - 08.09.2010
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
ROV navigation, motion estimation, SURF, phase correlation, benchmarking
Sažetak
The performance of different visual approaches for estimating the motion of an underwater Remotely Operated Vehicle (ROV) is discussed. The paper compares three different techniques: feature correlation, Speeded Up Robust Features (SURF), both based on feature extraction and matching, and phase correlation, which instead does not rely on image features. The three algorithms accuracy and performance are compared using a batch of data collected in typical operating conditions with the Romeo ROV. In estimating vehicle speed, phase correlation outperformed SURF in terms of robustness and precision, giving similar results to those obtained with feature correlation. In terms of computational time, phase correlation outperformed both feature-based methods.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Računarstvo
