Geometric descriptor for bag of visual words-based place recognition

John Stalbaum, Jae-Bok Song

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Bayesian pattern recognition is a natural companion for graph-based simultaneous localization and mapping (SLAM) due to its ability to come up with high quality place matches based solely on image data, completely eschewing metric information. Recent SLAM-like approaches such as fast appearance-based mapping (FAB-MAP) [1] are very effective information filters, with the ability to provide place matching data in real-time to a very high degree of accuracy. In this study, the strong foundations of FAB-MAP and bag of visual words-based place recognition are refined to include geometric information directly into the image descriptor. To demonstrate the practicality of such an approach, the new descriptor type was incorporated into a full real-time graph-based SLAM stack. In experiments, places are recognized at a rate of 14% in a series of experiments performed in challenging, visually monotonous environments, compared to the 9% rate obtained by the direct application of OpenFABMAP to the same data set [2]. The system played an instrumental role in maintaining map integrity, without which SLAM would not have been possible.

Original languageEnglish
Title of host publication2014 11th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages561-566
Number of pages6
ISBN (Electronic)9781479953325
DOIs
Publication statusPublished - 2014
Event2014 11th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2014 - Kuala Lumpur, Malaysia
Duration: 2014 Nov 122014 Nov 15

Other

Other2014 11th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2014
CountryMalaysia
CityKuala Lumpur
Period14/11/1214/11/15

Keywords

  • bag of visual words
  • computer vision
  • place recognition
  • SLAM

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction

Fingerprint Dive into the research topics of 'Geometric descriptor for bag of visual words-based place recognition'. Together they form a unique fingerprint.

  • Cite this

    Stalbaum, J., & Song, J-B. (2014). Geometric descriptor for bag of visual words-based place recognition. In 2014 11th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2014 (pp. 561-566). [7057391] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/URAI.2014.7057391