Direct sparse odometry with rolling shutter

David Schubert, Nikolaus Demmel, Vladyslav Usenko, Jörg Stückler, Daniel Cremers

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

5 Scopus citations


Neglecting the effects of rolling-shutter cameras for visual odometry (VO) severely degrades accuracy and robustness. In this paper, we propose a novel direct monocular VO method that incorporates a rolling-shutter model. Our approach extends direct sparse odometry which performs direct bundle adjustment of a set of recent keyframe poses and the depths of a sparse set of image points. We estimate the velocity at each keyframe and impose a constant-velocity prior for the optimization. In this way, we obtain a near real-time, accurate direct VO method. Our approach achieves improved results on challenging rolling-shutter sequences over state-of-the-art global-shutter VO.

Original languageEnglish
Title of host publicationComputer Vision – ECCV 2018 - 15th European Conference, 2018, Proceedings
EditorsVittorio Ferrari, Cristian Sminchisescu, Yair Weiss, Martial Hebert
PublisherSpringer Verlag
Number of pages16
ISBN (Print)9783030012366
StatePublished - 2018
Event15th European Conference on Computer Vision, ECCV 2018 - Munich, Germany
Duration: 8 Sep 201814 Sep 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11212 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference15th European Conference on Computer Vision, ECCV 2018


  • Direct monocular visual odometry
  • Rolling shutter


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