Semi-independent stereo visual odometry for different field of view cameras

Trong Phuc Truong, Vincent Nozick, Hideo Saito

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a pipeline for stereo visual odometry using cameras with different fields of view. It gives a proof of concept about how a constraint on the respective field of view of each camera can lead to both an accurate 3D reconstruction and a robust pose estimation. Indeed, when considering a fixed resolution, a narrow field of view has a higher angular resolution and can preserve image texture details. On the other hand, a wide field of view allows to track features over longer periods since the overlap between two successive frames is more substantial. We propose a semi-independent stereo system where each camera performs individually temporal multi-view optimization but their initial parameters are still jointly optimized in an iterative framework. Furthermore, the concept of lead and follow camera is introduced to adaptively propagate information between the cameras. We evaluate the method qualitatively on two indoor datasets, and quantitatively on a synthetic dataset to allow the comparison across different fields of view.

Original languageEnglish
Title of host publicationComputer Vision – ECCV 2018 Workshops, Proceedings
EditorsLaura Leal-Taixé, Stefan Roth
PublisherSpringer Verlag
Pages430-442
Number of pages13
ISBN (Print)9783030110086
DOIs
Publication statusPublished - 2019
Event15th European Conference on Computer Vision, ECCV 2018 - Munich, Germany
Duration: 2018 Sep 82018 Sep 14

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11129 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th European Conference on Computer Vision, ECCV 2018
CountryGermany
CityMunich
Period18/9/818/9/14

Keywords

  • 3D reconstruction
  • Field of view
  • Stereo visual odometry

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Truong, T. P., Nozick, V., & Saito, H. (2019). Semi-independent stereo visual odometry for different field of view cameras. In L. Leal-Taixé, & S. Roth (Eds.), Computer Vision – ECCV 2018 Workshops, Proceedings (pp. 430-442). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11129 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-11009-3_26