PHROG: A Multimodal Feature for Place Recognition

Sensors
Fabien BonardiPascal Vasseur

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 aBag-of-Wordsapproach. 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 ...Continue Reading

References

Oct 22, 2005·IEEE Transactions on Pattern Analysis and Machine Intelligence·Krystian Mikolajczyk, Cordelia Schmid
Apr 14, 2007·IEEE Transactions on Pattern Analysis and Machine Intelligence·Andrew J DavisonOlivier Stasse
Feb 26, 2014·Sensors·Pablo RicaurteAngel D Sappa

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Citations

May 23, 2020·Sensors·Shaorong XieShihui Ying

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Methods Mentioned

BETA
feature extraction

Software Mentioned

monoSLAM
Ubuntu
SIFT OpenCV
PHROG
SURF

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