Keyframe and inlier selection for visual SLAM

John Stalbaum, Jae Bok Song

Research output: Contribution to conferencePaper

5 Citations (Scopus)

Abstract

Using stereo cameras to perform Simultaneous Localization and Mapping (SLAM) is an active area of mobile robotics research with many applications. Regardless of which SLAM algorithm is used for an application, the quality of the results depends heavily on the quality and consistency of the data going into the algorithm. In this study, a novel algorithm for inlier and keyframe selection is used to produce sets of observations that can be used to perform SLAM. Several simulations are performed using data sets captured in large outdoor environments, and the results are evaluated in terms of physical consistency, covisibility between frames, and SLAM results. The results obtained from these simulations suggest that the algorithm can be useful in the implementation of SLAM.

Original languageEnglish
Pages391-396
Number of pages6
DOIs
Publication statusPublished - 2013
Event2013 10th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2013 - Jeju, Korea, Republic of
Duration: 2013 Oct 302013 Nov 2

Other

Other2013 10th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2013
CountryKorea, Republic of
CityJeju
Period13/10/3013/11/2

Keywords

  • bundle adjustment
  • inlier selection
  • keyframe selection
  • SLAM
  • visual feature extaction

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction

Fingerprint Dive into the research topics of 'Keyframe and inlier selection for visual SLAM'. Together they form a unique fingerprint.

  • Cite this

    Stalbaum, J., & Song, J. B. (2013). Keyframe and inlier selection for visual SLAM. 391-396. Paper presented at 2013 10th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2013, Jeju, Korea, Republic of. https://doi.org/10.1109/URAI.2013.6677295