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Recognition of Fuzzy or Incompletely Described Objects Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Frame-to-Frame Visual Odometry: The Importance of Local Transformations

Author : Aleksander Kostusiak

Published in: Proceedings of the 10th International Conference on Computer Recognition Systems CORES 2017

Publisher: Springer International Publishing

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Abstract

Trajectory estimation is of pivotal importance for mobile robots. Visual Odometry (VO) allows localizing a robot from passive vision data in frame-to-frame fashion. The VO problem can be solved in different ways, hence an evaluation of these algorithms in the context of real benchmark data is interesting. We focus on feature-based n-point methods based on RGB images. These methods used in monocular vision allow for camera rotation estimation, but only a few of them provide translation estimates up to the unknown scale. In the context of the use of commodity RGB-D cameras, we also compare these methods with the Kabsch algorithm, which uses full depth information.

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Metadata
Title
Frame-to-Frame Visual Odometry: The Importance of Local Transformations
Author
Aleksander Kostusiak
Copyright Year
2018
Book
Proceedings of the 10th International Conference on Computer Recognition Systems CORES 2017

Print ISBN: 978-3-319-59161-2

Electronic ISBN: 978-3-319-59162-9

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-59162-9_37

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