Auto-calibration and synchronization of camera and MEMS-sensors
This article describes our ongoing research on auto-calibration and synchronization of camera and MEMS-sensors. The research is applicable on any system that consists of camera and MEMS-sensors, such as gyroscope. The main task of our research is to find such parameters as the focal length of camera...
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Ivannikov Institute for System Programming of the Russian Academy of Sciences
2018-10-01
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Online Access: | https://ispranproceedings.elpub.ru/jour/article/view/562 |
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doaj-6dd9abe1c04d461e829570fc786d69a62020-11-25T01:34:54Zeng Ivannikov Institute for System Programming of the Russian Academy of SciencesТруды Института системного программирования РАН2079-81562220-64262018-10-0130416918210.15514/ISPRAS-2018-30(4)-11562Auto-calibration and synchronization of camera and MEMS-sensorsA. R. Polyakov0A. V. Kornilova1I. A. Kirilenko2Санкт-Петербургский Государственный УниверситетСанкт-Петербургский Государственный УниверситетСанкт-Петербургский Государственный УниверситетThis article describes our ongoing research on auto-calibration and synchronization of camera and MEMS-sensors. The research is applicable on any system that consists of camera and MEMS-sensors, such as gyroscope. The main task of our research is to find such parameters as the focal length of camera and the time offset between sensor timestamps and frame timestamps, which is caused by frame processing and encoding. This auto-calibration makes possible to scale computer vision algorithms (video stabilization, 3D reconstruction, video compression, augmented reality), which use frames and sensor’s data, to a wider range of devices equipped with a camera and MEMS-sensors. In addition, auto-calibration allows completely abstracting from the characteristics of a particular device and developing algorithms that work on different platforms (mobile platforms, embedded systems, action cameras) independently of concrete device’s characteristics as well. The article describes the general mathematical model needed to implement such a functionality using computer vision techniques and MEMS-sensors readings. The authors present a review and comparison of existing approaches to auto-calibration and propose own improvements for these methods, which increase the quality of previous works and applicable for a general model of video stabilization algorithm with MEMS-sensors.https://ispranproceedings.elpub.ru/jour/article/view/562калибровка камерыавтоматическая калибровкаобработка цифровых сигналовкомпьютерное зрение |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
A. R. Polyakov A. V. Kornilova I. A. Kirilenko |
spellingShingle |
A. R. Polyakov A. V. Kornilova I. A. Kirilenko Auto-calibration and synchronization of camera and MEMS-sensors Труды Института системного программирования РАН калибровка камеры автоматическая калибровка обработка цифровых сигналов компьютерное зрение |
author_facet |
A. R. Polyakov A. V. Kornilova I. A. Kirilenko |
author_sort |
A. R. Polyakov |
title |
Auto-calibration and synchronization of camera and MEMS-sensors |
title_short |
Auto-calibration and synchronization of camera and MEMS-sensors |
title_full |
Auto-calibration and synchronization of camera and MEMS-sensors |
title_fullStr |
Auto-calibration and synchronization of camera and MEMS-sensors |
title_full_unstemmed |
Auto-calibration and synchronization of camera and MEMS-sensors |
title_sort |
auto-calibration and synchronization of camera and mems-sensors |
publisher |
Ivannikov Institute for System Programming of the Russian Academy of Sciences |
series |
Труды Института системного программирования РАН |
issn |
2079-8156 2220-6426 |
publishDate |
2018-10-01 |
description |
This article describes our ongoing research on auto-calibration and synchronization of camera and MEMS-sensors. The research is applicable on any system that consists of camera and MEMS-sensors, such as gyroscope. The main task of our research is to find such parameters as the focal length of camera and the time offset between sensor timestamps and frame timestamps, which is caused by frame processing and encoding. This auto-calibration makes possible to scale computer vision algorithms (video stabilization, 3D reconstruction, video compression, augmented reality), which use frames and sensor’s data, to a wider range of devices equipped with a camera and MEMS-sensors. In addition, auto-calibration allows completely abstracting from the characteristics of a particular device and developing algorithms that work on different platforms (mobile platforms, embedded systems, action cameras) independently of concrete device’s characteristics as well. The article describes the general mathematical model needed to implement such a functionality using computer vision techniques and MEMS-sensors readings. The authors present a review and comparison of existing approaches to auto-calibration and propose own improvements for these methods, which increase the quality of previous works and applicable for a general model of video stabilization algorithm with MEMS-sensors. |
topic |
калибровка камеры автоматическая калибровка обработка цифровых сигналов компьютерное зрение |
url |
https://ispranproceedings.elpub.ru/jour/article/view/562 |
work_keys_str_mv |
AT arpolyakov autocalibrationandsynchronizationofcameraandmemssensors AT avkornilova autocalibrationandsynchronizationofcameraandmemssensors AT iakirilenko autocalibrationandsynchronizationofcameraandmemssensors |
_version_ |
1725069739563155456 |