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TUM Department of Informatics
Technical University of Munich

Technical University of Munich

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Informatik IX
Chair of Computer Vision & Artificial Intelligence

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

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CVG Group DVL Group

News

02.10.2020

We have five papers accepted to 3DV 2020!

30.09.2020

Our effcient deep network architectures form the AI engine of the project Slow Down COVID-19 at Harvard.

24.07.2020

Our practical course "Vision-based Navigation" (WS18, SS19) by Dr. Vladyslav Usenko and Nikolaus Demmel was honored as best practical course in the academic year 2018/2019 by the department for Informatics.

07.05.2020

We are organizing a workshop on Map-based Localization for Autonomous Driving at ECCV 2020, Glasgow, UK.

13.04.2020

Daniel Cremers received an ERC Advanced Grant (3.5 Mio Euro) for pioneering frontier research from the European Research Council. This constitutes his fifth ERC grant.

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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
2019
[]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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Dataset

Calibration

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.

SequenceBagEuroc/DSO
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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Informatik IX
Chair of Computer Vision & Artificial Intelligence

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

Follow us on:
CVG Group DVL Group

News

02.10.2020

We have five papers accepted to 3DV 2020!

30.09.2020

Our effcient deep network architectures form the AI engine of the project Slow Down COVID-19 at Harvard.

24.07.2020

Our practical course "Vision-based Navigation" (WS18, SS19) by Dr. Vladyslav Usenko and Nikolaus Demmel was honored as best practical course in the academic year 2018/2019 by the department for Informatics.

07.05.2020

We are organizing a workshop on Map-based Localization for Autonomous Driving at ECCV 2020, Glasgow, UK.

13.04.2020

Daniel Cremers received an ERC Advanced Grant (3.5 Mio Euro) for pioneering frontier research from the European Research Council. This constitutes his fifth ERC grant.

More