NDLI: Graph-based visual SLAM and visual odometry using an RGB-D camera

Content Provider	IEEE Xplore Digital Library
Author	Klussendorff, J.H. Hartmann, J. Forouher, D. Maehle, E.
Copyright Year	2013
Description	Author affiliation: Inst. of Comput. Eng., Univ. of Luebeck, Luebeck, Germany (Klussendorff, J.H.; Hartmann, J.; Forouher, D.; Maehle, E.)
Abstract	In this paper we present a real-time graph-based visual SLAM approach. The presented visual SLAM algorithm can be separated into three parts: feature extraction, data association, and SLAM back-end. We use FAST for feature detection and the Binary Robust Independent Elementary Features (BRIEF) as feature descriptor, which together provide a fast and stable feature extraction. The data association is solved using Locality Sensitive Hashing (LSH), which uses local hash tables and profits from binary feature descriptors. As SLAM back-end we use the general graph optimization framework $g^{2}o,$ which is designed to provide solutions to several SLAM variants. We further provide a novel approach to visual odometry by combining recent sensor measurements into a small pose graph and optimizing it using $g^{2}o.$ For finding potential neighbour nodes and loop closures we introduce the Global Feature Repository (GFR). GFR searches for loop closures and potential neighbours independent of their position in the graph. Finally, we show the accuracy and real-time ability of our algorithm by comparing it to a recently published benchmark dataset. We further provide some large-scale datasets using state-of-the-art laser localization as ground-truth.
Starting Page	288
Ending Page	293
File Size	379732
Page Count	6
File Format	PDF
e-ISBN	9781467355117
DOI	10.1109/RoMoCo.2013.6614623
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-03
Publisher Place	Poland
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Simultaneous localization and mapping Visualization Feature extraction Cameras Optimization Real-time systems
Content Type	Text
Resource Type	Article

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