Rolling Shutter Correction in Manhattan World

Pulak Purkait, Christopher Zach, Ales Leonardis

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

10 Citations (Scopus)
312 Downloads (Pure)


A vast majority of consumer cameras operate the rolling shutter mechanism, which often produces distorted images due to inter-row delay while capturing an image. Recent methods for monocular rolling shutter compensation utilize blur kernel, straightness of line segments, as well as angle and length preservation. However, they do not incorporate scene geometry explicitly for rolling shutter correction, therefore, information about the 3D scene geometry is
often distorted by the correction process. In this paper we propose a novel method which leverages geometric properties of the scene—in particular vanishing directions—to estimate the camera motion during rolling shutter exposure from a single distorted image. The proposed method jointly estimates the orthogonal vanishing directions and the rolling shutter camera motion. We performed extensive experiments on synthetic and real datasets which demonstrate the benefits of our approach both in terms of qualitative and quantitative results (in terms of a geometric structure fitting) as well as with respect to computation time.
Original languageEnglish
Title of host publicationProceedings of the International Conference on Computer Vision (ICCV 2017)
PublisherIEEE Computer Society Press
Number of pages9
ISBN (Electronic)9781538610329
ISBN (Print)9781538610336
Publication statusPublished - 25 Dec 2017
EventInternational Conference on Computer Vision (ICCV 2017) - Venice, Italy
Duration: 22 Oct 201729 Oct 2017

Publication series

NameIEEE International Conference on Computer Vision (ICCV)
ISSN (Electronic)2380-7504


ConferenceInternational Conference on Computer Vision (ICCV 2017)


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