TY - JOUR

T1 - Auto-calibration and synchronization of camera and MEMS-sensors

AU - Polyakov, A.R.

AU - Kornilova, A.V.

AU - Kirilenko, I.A.

PY - 2018

Y1 - 2018

N2 - 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.

AB - 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.

KW - CAMERA CALIBRATION

KW - DIGITAL SIGNAL PROCESSING

KW - COMPUTER VISION

M3 - Article

VL - 30

SP - 169

EP - 182

JO - Труды института системного программирования РАН

JF - Труды института системного программирования РАН

SN - 2079-8156

IS - 4

ER -