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...

Full description

Bibliographic Details
Main Authors: A. R. Polyakov, A. V. Kornilova, I. A. Kirilenko
Format: Article
Language:English
Published: Ivannikov Institute for System Programming of the Russian Academy of Sciences 2018-10-01
Series:Труды Института системного программирования РАН
Subjects:
Online Access:https://ispranproceedings.elpub.ru/jour/article/view/562
id doaj-6dd9abe1c04d461e829570fc786d69a6
record_format Article
spelling 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