Journal ArticleDOI
Appearance-only SLAM at large scale with FAB-MAP 2.0
Mark Cummins,Paul Newman +1 more
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TLDR
A new formulation of appearance-only SLAM suitable for very large scale place recognition that incorporates robustness against perceptual aliasing and substantially outperforms the standard term-frequency inverse-document-frequency (tf-idf) ranking measure.Abstract:
We describe a new formulation of appearance-only SLAM suitable for very large scale place recognition. The system navigates in the space of appearance, assigning each new observation to either a new or a previously visited location, without reference to metric position. The system is demonstrated performing reliable online appearance mapping and loop-closure detection over a 1000âkm trajectory, with mean filter update times of 14âms. The scalability of the system is achieved by defining a sparse approximation to the FAB-MAP model suitable for implementation using an inverted index. Our formulation of the problem is fully probabilistic and naturally incorporates robustness against perceptual aliasing. We also demonstrate that the approach substantially outperforms the standard term-frequency inverse-document-frequency (tf-idf) ranking measure. The 1000âkm data set comprising almost a terabyte of omni-directional and stereo imagery is available for use, and we hope that it will serve as a benchmark for future systems.read more
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Journal ArticleDOI
ORB-SLAM: A Versatile and Accurate Monocular SLAM System
TL;DR: ORB-SLAM as discussed by the authors is a feature-based monocular SLAM system that operates in real time, in small and large indoor and outdoor environments, with a survival of the fittest strategy that selects the points and keyframes of the reconstruction.
Journal ArticleDOI
ORB-SLAM: a Versatile and Accurate Monocular SLAM System
TL;DR: A survival of the fittest strategy that selects the points and keyframes of the reconstruction leads to excellent robustness and generates a compact and trackable map that only grows if the scene content changes, allowing lifelong operation.
Journal ArticleDOI
Bags of Binary Words for Fast Place Recognition in Image Sequences
TL;DR: A vocabulary tree is built that discretizes a binary descriptor space and uses the tree to speed up correspondences for geometrical verification, and presents competitive results with no false positives in very different datasets.
Journal ArticleDOI
Visual Place Recognition: A Survey
Stephanie Lowry,Niko Sünderhauf,Paul Newman,John J. Leonard,David D. Cox,Peter Corke,Michael Milford +6 more
TL;DR: A survey of the visual place recognition research landscape is presented, introducing the concepts behind place recognition, how a “place” is defined in a robotics context, and the major components of a place recognition system.
Journal ArticleDOI
3-D Mapping With an RGB-D Camera
TL;DR: A novel mapping system that robustly generates highly accurate 3-D maps using an RGB-D camera that applies to small domestic robots such as vacuum cleaners, as well as flying robotssuch as quadrocopters.
References
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Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography
TL;DR: New results are derived on the minimum number of landmarks needed to obtain a solution, and algorithms are presented for computing these minimum-landmark solutions in closed form that provide the basis for an automatic system that can solve the Location Determination Problem under difficult viewing.
Journal ArticleDOI
The anatomy of a large-scale hypertextual Web search engine
Sergey Brin,Lawrence Page +1 more
TL;DR: This paper provides an in-depth description of Google, a prototype of a large-scale search engine which makes heavy use of the structure present in hypertext and looks at the problem of how to effectively deal with uncontrolled hypertext collections where anyone can publish anything they want.
Journal Article
The Anatomy of a Large-Scale Hypertextual Web Search Engine.
Sergey Brin,Lawrence Page +1 more
TL;DR: Google as discussed by the authors is a prototype of a large-scale search engine which makes heavy use of the structure present in hypertext and is designed to crawl and index the Web efficiently and produce much more satisfying search results than existing systems.
Book ChapterDOI
SURF: speeded up robust features
TL;DR: A novel scale- and rotation-invariant interest point detector and descriptor, coined SURF (Speeded Up Robust Features), which approximates or even outperforms previously proposed schemes with respect to repeatability, distinctiveness, and robustness, yet can be computed and compared much faster.
Book
Introduction to Information Retrieval
TL;DR: In this article, the authors present an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections.