iBoW-LCD: An Appearance-Based Loop-Closure Detection Approach Using Incremental Bags of Binary Words

In this letter, we introduce iBoW-LCD, a novel appearance-based loop-closure detection method. The presented approach makes use of an incremental bag-of-words (BoW) scheme based on binary descriptors to retrieve previously seen similar images, avoiding any vocabulary training stage usually required...

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Bibliographic Details
Published inIEEE robotics and automation letters Vol. 3; no. 4; pp. 3051 - 3057
Main Authors Garcia-Fidalgo, Emilio, Ortiz, Alberto
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 01.10.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Closures
Dictionaries
Indexing
Indoor environments
localization
Mapping
Simultaneous localization and mapping
Training
visual-based navigation
Visualization
Vocabulary
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Summary:In this letter, we introduce iBoW-LCD, a novel appearance-based loop-closure detection method. The presented approach makes use of an incremental bag-of-words (BoW) scheme based on binary descriptors to retrieve previously seen similar images, avoiding any vocabulary training stage usually required by classic BoW models. In addition, to detect loop closures, iBoW-LCD builds on the concept of dynamic islands, a simple but effective mechanism to group similar images close in time, which reduces the computational times typically associated with Bayesian frameworks. Our approach is validated using several indoor and outdoor public datasets, taken under different environmental conditions, achieving a high accuracy and outperforming other state-of-the-art solutions.
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ISSN:2377-3766
2377-3766
DOI:10.1109/LRA.2018.2849609