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Robust structure from motion estimation using inertial data.

Authors
  • 1
Type
Published Article
Journal
Journal of the Optical Society of America. A, Optics, image science, and vision
Publication Date
Volume
18
Issue
12
Pages
2982–2997
Identifiers
PMID: 11760197
Source
Medline

Abstract

The utility of using inertial data for the structure-from-motion (SfM) problem is addressed. We show how inertial data can be used for improved noise resistance, reduction of inherent ambiguities, and handling of mixed-domain sequences. We also show that the number of feature points needed for accurate and robust SfM estimation can be significantly reduced when inertial data are employed. Cramér-Rao lower bounds are computed to quantify the improvements in estimating motion parameters. A robust extended-Kalman-filter-based SfM algorithm using inertial data is then developed to fully exploit the inertial information. This algorithm has been tested by using synthetic and real image sequences, and the results show the efficacy of using inertial data for the SfM problem.

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