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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.

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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]
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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 manufacturer, the time difference of two consecutive rows due to rolling shutter is approximately 29.4737 microseconds.

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


Thomas Pock (TU Graz) will give a talk in the TUM AI lecture series on April 15th, 3pm! Livestream


Max Welling (University of Amsterdam) will give a talk in the TUM AI lecture series on April 1st, 3pm! Livestream


We have seven papers (4 orals, 3 posters) accepted to CVPR 2021!


We have two papers accepted to ICRA 2021!