English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Modern automotive vehicles are often equipped with a budget commercialrolling shutter camera. These devices often produce distorted images due to theinter-row delay of the camera while capturing the image. Recent methods formonocular rolling shutter motion compensation utilize blur kernel and thestraightness property of line segments. However, these methods are limited tohandling rotational motion and also are not fast enough to operate in realtime. In this paper, we propose a minimal solver for the rolling shutter motioncompensation which assumes known vertical direction of the camera. Thanks tothe Ackermann motion model of vehicles which consists of only two motionparameters, and two parameters for the simplified depth assumption that lead toa 4-line algorithm. The proposed minimal solver estimates the rolling shuttercamera motion efficiently and accurately. The extensive experiments on real andsimulated datasets demonstrate the benefits of our approach in terms ofqualitative and quantitative results.

Minimal Solvers for Monocular Rolling Shutter Compensation under Ackermann Motion