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Proceedings Paper

A comparative study of image feature detection and description methods for robot vision
Author(s): Martin Gonzalez-Ruiz; Victor H. Diaz-Ramirez; Rigoberto Juarez-Salazar
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Paper Abstract

Detection and description of local features in images is an essential task in robot vision. This task allows to identify and uniquely specify stable and invariant regions in a observed scene. Many successful detectors and descriptors have been proposed. However, the proper combination of a detector and a descriptor is not trivial because there is a trade-off among different performance criteria. This work presents a comparative study of successful image feature detection and description methods in the context of the simultaneous localization and mapping problem. The considered methods are exhaustively evaluated in terms of accuracy, robustness, and processing time.

Paper Details

Date Published: 6 September 2019
PDF: 6 pages
Proc. SPIE 11136, Optics and Photonics for Information Processing XIII, 111360P (6 September 2019); doi: 10.1117/12.2528581
Show Author Affiliations
Martin Gonzalez-Ruiz, Instituto Politécnico Nacional - CITEDI (Mexico)
Victor H. Diaz-Ramirez, Instituto Politécnico Nacional - CITEDI (Mexico)
Rigoberto Juarez-Salazar, CONACYT - Instituto Politécnico Nacional - CITEDI (Mexico)

Published in SPIE Proceedings Vol. 11136:
Optics and Photonics for Information Processing XIII
Khan M. Iftekharuddin; Abdul A. S. Awwal; Victor H. Diaz-Ramirez; Andrés Márquez, Editor(s)

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