Next Article in Journal
Fully-Polymeric pH Sensor Realized by Means of a Single-Step Soft Embossing Technique
Previous Article in Journal
An Adaptive Orientation Estimation Method for Magnetic and Inertial Sensors in the Presence of Magnetic Disturbances
Article Menu
Issue 5 (May) cover image

Export Article

Open AccessArticle
Sensors 2017, 17(5), 1167; doi:10.3390/s17051167

PHROG: A Multimodal Feature for Place Recognition

1
Laboratoire d’Informatique, de Traitement de l’Information et des Systèmes, Normandie University, UNIROUEN, UNIHAVRE, INSA Rouen, LITIS, 76000 Rouen, France
2
Institut de Recherche en Systèmes Électroniques Embarqués, Normandie University, UNIROUEN, ESIGELEC, IRSEEM, 76000 Rouen, France
3
Centre d’Études et d’Expertise sur les Risques, l’Environnement, la Mobilité et l’Aménagement, CEREMA, 76000 Rouen, France
*
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M.N. Passaro
Received: 3 March 2017 / Revised: 17 May 2017 / Accepted: 18 May 2017 / Published: 20 May 2017
(This article belongs to the Section Physical Sensors)

Abstract

Long-term place recognition in outdoor environments remains a challenge due to high appearance changes in the environment. The problem becomes even more difficult when the matching between two scenes has to be made with information coming from different visual sources, particularly with different spectral ranges. For instance, an infrared camera is helpful for night vision in combination with a visible camera. In this paper, we emphasize our work on testing usual feature point extractors under both constraints: repeatability across spectral ranges and long-term appearance. We develop a new feature extraction method dedicated to improve the repeatability across spectral ranges. We conduct an evaluation of feature robustness on long-term datasets coming from different imaging sources (optics, sensors size and spectral ranges) with a Bag-of-Words approach. The tests we perform demonstrate that our method brings a significant improvement on the image retrieval issue in a visual place recognition context, particularly when there is a need to associate images from various spectral ranges such as infrared and visible: we have evaluated our approach using visible, Near InfraRed (NIR), Short Wavelength InfraRed (SWIR) and Long Wavelength InfraRed (LWIR). View Full-Text
Keywords: feature extraction; cross-spectral imaging; scene matching; visual place recognition feature extraction; cross-spectral imaging; scene matching; visual place recognition
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Bonardi, F.; Ainouz, S.; Boutteau, R.; Dupuis, Y.; Savatier, X.; Vasseur, P. PHROG: A Multimodal Feature for Place Recognition. Sensors 2017, 17, 1167.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top