Methods for combined monocular and stereo mobile robot localization

Authors:
Friedrich Fraundorfer;Changchang Wu;Marc Pollefeys
Affiliations:
Department of Computer Science, ETH Zürich, Switzerland;Department of Computer Science, University of North Carolina at Chapel Hill;Department of Computer Science, ETH Zürich, Switzerland
Venue:
ICPR'10 Proceedings of the 20th International conference on Recognizing patterns in signals, speech, images, and videos
Year:
2010

Citing 7
Cited 0

Indoor robot motion based on monocular images

Robotica
Distinctive Image Features from Scale-Invariant Keypoints

International Journal of Computer Vision
Scalable Recognition with a Vocabulary Tree

CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
FAB-MAP: Probabilistic Localization and Mapping in the Space of Appearance

International Journal of Robotics Research
COLD: The CoSy Localization Database

International Journal of Robotics Research
Combining Monocular and Stereo Cues for Mobile Robot Localization Using Visual Words

ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Fast and Incremental Method for Loop-Closure Detection Using Bags of Visual Words

IEEE Transactions on Robotics

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper describes an approach for mobile robot localization using a visual word based place recognition approach. In our approach we exploit the benefits of a stereo camera system for place recognition. Visual words computed from SIFT features are combined with VIP (viewpoint invariant patches) features that use depth information from the stereo setup. The approach was evaluated under the ImageCLEF@ICPR 2010 competition1. The results achieved on the competition datasets are published in this paper.