Direkt zum Inhalt springen
Computer Vision Group
TUM Department of Informatics
Technical University of Munich

Technical University of Munich



Rolling-Shutter Visual-Inertial Odometry Dataset

Contact : David Schubert, Nikolaus Demmel, Lukas von Stumberg, Vladyslav Usenko.

We present a novel dataset that contains time-synchronized global-shutter and rolling-shutter images, IMU data and ground-truth poses for ten different sequences.

Export as PDF, XML, TEX or BIB

Conference and Workshop Papers
[]Rolling-Shutter Modelling for Visual-Inertial Odometry (D. Schubert, N. Demmel, L. von Stumberg, V. Usenko and D. Cremers), In International Conference on Intelligent Robots and Systems (IROS), 2019. ([arxiv]) [bibtex] [pdf]
Powered by bibtexbrowser
Export as PDF, XML, TEX or BIB



For the calibrated sequences that are provided in the table the ground-truth poses are provided in the IMU coordinate frame and time-synchronized with image and IMU data. Geometric camera-IMU calibration can be found here: calibration.yaml. Calibration was done using the following sequences.

Camera calibration dataset-calib-cam1.bag dataset-calib-cam1.tar
IMU calibration dataset-calib-imu1.bag dataset-calib-imu1.tar

Note that for the calibration sequences, both cameras were operating in global-shutter mode. This means the timestamps for the rolling-shutter images refer to the first row. In general, timestamps denote the middle of the exposure interval.

For more information about calibration, we refer to our visual-inertial dataset.

According to the camera manufacturer, the time difference of two consecutive rows due to rolling shutter can't be read directly, but is very well approximated by the step size of the exposure time. Like this, we obtain an approximate row time difference of 29.4737 microseconds.

Rechte Seite

Informatik IX
Chair of Computer Vision & Artificial Intelligence

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

Follow us on:
CVG Group DVL Group



Bernt Schiele (Max Planck Institute for Informatics) will give a talk in the TUM AI lecture series on June 10th, 3pm! Livestream

French-German Machine Learning Symposium

French-German Machine Learning Symposium

The French-German Machine Learning Symposium aims to strengthen interactions and inspire collaborations between both countries. We invited some of the leading ML researchers from France and Germany to this two-day symposium to give a glimpse into their research, and engage in discussions on the future of machine learning and how to strengthen research collaborations in ML between France and Germany.

The list of speakers includes Yann LeCun, Cordelia Schmid, Jean-Bernard Lasserre, Bernhard Schölkopf, and many more! For the full program please visit the webpage.


Ron Kimmel (Technion - Israel Institute of Technology) will give a talk in the TUM AI lecture series on May 6th, 3pm! Livestream


4Seasons Dataset: We have released a novel dataset for benchmarking multi-weather SLAM in autonomous driving.


Hao Li (Pinscreen) will give a talk in the TUM AI lecture series on April 22nd, 8pm! Livestream