Multistate Constrained Invariant Kalman Filter for Rolling Shutter Camera and Imu Calibration

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Abstract

In this paper, we propose a novel algorithm for joint calibration of a rolling shutter camera and inertial sensors. Specifically, the proposed method performs online calibration to estimate the camera intrinsics, the readout time, the extrinsics and the time offset between the camera and the IMU, as well as IMU's bias. By employing a multi-state constrained invariant Kalman filter, the proposed method processes the measurements of IMU and rolling shutter camera in a decoupled way, which greatly reduces the computational complexity of Jacobian matrices and further improves the robustness and accuracy. Experiments on public datasets demonstrate that the proposed approach can accurately calibrate the considered parameters and perform better than state-of-the-art methods in terms of accuracy and robustness.
Original languageEnglish
Title of host publicationProceedings of 2020 IEEE International Conference on Image Processing
PublisherIEEE
Publication date2020
Pages56-60
ISBN (Electronic)978-1-7281-6395-6
DOIs
Publication statusPublished - 2020
Event2020 IEEE International Conference on Image Processing - Virtual conference, Abu Dhabi, United Arab Emirates
Duration: 25 Sep 202028 Sep 2020

Conference

Conference2020 IEEE International Conference on Image Processing
LocationVirtual conference
CountryUnited Arab Emirates
CityAbu Dhabi
Period25/09/202028/09/2020
SeriesInternational Conference on Image Processing. Proceedings
ISSN1522-4880

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