Error propagation in monocular navigation for Z compared to eightpoint algorithm

Elmar Mair, Michael Suppa, Darius Burschka

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

Efficient visual pose estimation plays an important role for a variety of applications. To improve the quality, the measurements from different sensors can be fused. However, a reliable fusion requires the knowledge of the uncertainty of each estimate. In this work, we provide an error analysis for the Z algorithm. Furthermore, we extend the existing first-order error propagation for the 8-point algorithm to allow for feature normalization, as proposed by Hartley or Muhlich, and the rotation matrix based decomposition. Both methods are efficient visual odometry techniques which allow high frame-rates and, thus, dynamic motions in unbounded workspaces. Finally, we provide experiments which validate the accuracy of the error propagation and which enable a brief comparison, showing that the Z significantly outperforms the 8-point algorithm. We also discuss the influence of the number of features, the aperture angle, and the image resolution on the accuracy of the pose estimation.

Original languageEnglish
Title of host publicationIROS 2013
Subtitle of host publicationNew Horizon, Conference Digest - 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems
Pages4220-4227
Number of pages8
DOIs
StatePublished - 2013
Event2013 26th IEEE/RSJ International Conference on Intelligent Robots and Systems: New Horizon, IROS 2013 - Tokyo, Japan
Duration: 3 Nov 20138 Nov 2013

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Conference

Conference2013 26th IEEE/RSJ International Conference on Intelligent Robots and Systems: New Horizon, IROS 2013
Country/TerritoryJapan
CityTokyo
Period3/11/138/11/13

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