NDLI: Parsimonious loop-closure detection based on global image-descriptors of panoramic images

Content Provider	IEEE Xplore Digital Library
Author	Gerstmayr-Hillen, L. Schluter, O. Krzykawski, M. Moller, R.
Copyright Year	2011
Description	Author affiliation: Computer Engineering Group, Faculty of Technology, Bielefeld University, 33501 Bielefeld, Germany (Gerstmayr-Hillen, L.; Schluter, O.; Krzykawski, M.; Moller, R.)
Abstract	In the context of vision-based topological navigation, detecting loop closures requires to compare the robot's current camera image to a large number of images stored in the map. For efficient image comparisons, we apply distance functions to global image-descriptors, i.e. low-dimensional descriptors derived from the entire panoramic images. To identify promising combinations of descriptors and distance functions, we formulate the loop-closure detection as a binary classification problem and analyze the resulting receiver operator characteristics (ROC). The results of comparing a wide range of descriptors and distance functions reveal that reliable loop-closure detection is possible with a single 16- to 128-dimensional image-descriptor based on gray-value histograms or Fourier descriptors and that all considered distance functions have a comparable performance.
Starting Page	576
Ending Page	581
File Size	322030
Page Count	6
File Format	PDF
ISBN	9781457711589
e-ISBN	9781457711596
DOI	10.1109/ICAR.2011.6088548
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-06-20
Publisher Place	Estonia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robots Databases Frequency control Histograms Navigation Lighting Vectors
Content Type	Text
Resource Type	Article

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