Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Pavel Davidson"'
Publikováno v:
Sensors, Vol 23, Iss 4, p 2249 (2023)
Oxygen uptake (V˙O2) is an important metric in any exercise test including walking and running. It can be measured using portable spirometers or metabolic analyzers. Those devices are, however, not suitable for constant use by consumers due to their
Externí odkaz:
https://doaj.org/article/6529578ca04a4e8b911ea92a2b550ed7
Publikováno v:
Sensors, Vol 21, Iss 4, p 1553 (2021)
Vertical ground reaction force (vGRF) can be measured by force plates or instrumented treadmills, but their application is limited to indoor environments. Insoles remove this restriction but suffer from low durability (several hundred hours). Therefo
Externí odkaz:
https://doaj.org/article/2df498438cef4f848172bb248a7b5cca
Publikováno v:
Remote Sensing, Vol 13, Iss 3, p 388 (2021)
In this paper, an EKF (Extended Kalman Filter)-based algorithm is proposed to estimate 3D position and velocity components of different cars in a scene by fusing the semantic information and car model, extracted from successive frames with camera mot
Externí odkaz:
https://doaj.org/article/80d5c0367d854de2912cc9e152630fe4
Publikováno v:
Remote Sensing, Vol 11, Iss 17, p 1990 (2019)
Binocular disparity and motion parallax are the most important cues for depth estimation in human and computer vision. Here, we present an experimental study to evaluate the accuracy of these two cues in depth estimation to stationary objects in a st
Externí odkaz:
https://doaj.org/article/bd4646e8f9d846f28c7d036c74113360
Publikováno v:
Sensors, Vol 19, Iss 6, p 1480 (2019)
This paper describes a single body-mounted sensor that integrates accelerometers, gyroscopes, compasses, barometers, a GPS receiver, and a methodology to process the data for biomechanical studies. The sensor and its data processing system can accura
Externí odkaz:
https://doaj.org/article/68e43851c76a4db6ae75eef086dc2b8d
Publikováno v:
Remote Sensing; Volume 13; Issue 3; Pages: 388
In this paper, an EKF (Extended Kalman Filter)-based algorithm is proposed to estimate 3D position and velocity components of different cars in a scene by fusing the semantic information and car model, extracted from successive frames with camera mot
Publikováno v:
Remote Sensing; Volume 11; Issue 17; Pages: 1990
Binocular disparity and motion parallax are the most important cues for depth estimation in human and computer vision. Here, we present an experimental study to evaluate the accuracy of these two cues in depth estimation to stationary objects in a st
Publikováno v:
2019 26th Saint Petersburg International Conference on Integrated Navigation Systems (ICINS).
We propose a method to estimate the distance to objects based on the complementary nature of monocular image sequences and camera kinematic parameters. The fusion of camera measurements with the kinematics parameters that are measured by an IMU and a
Autor:
Pavel Davidson, M. Mansour, Jukka-Pekka Raunio, Oleg A. Stepanov, Robert Piche, Mohammad M. Aref
—: We propose a method to estimate the distance to objects based on the complementary nature of monocular image sequences and camera kinematic parameters. The fusion of camera measurements with the kinematics parameters that are measured by an IMU
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e2418fc35c72386493fea35e1f06fe2e
https://trepo.tuni.fi/handle/10024/130432
https://trepo.tuni.fi/handle/10024/130432
Publikováno v:
Handbook of Signal Processing Systems ISBN: 9783319917337
Handbook of Signal Processing Systems ISBN: 9781461468585
Handbook of Signal Processing Systems
Handbook of Signal Processing Systems ISBN: 9781461468585
Handbook of Signal Processing Systems
Due to the universal presence of motion, vibration, and shock, inertial motion sensors can be applied in various contexts. Development of the microelectromechanical (MEMS) technology opens up many new consumer and industrial applications for accelero
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0959e3a52bbb84450c82cef8272a7565
https://doi.org/10.1007/978-3-319-91734-4_2
https://doi.org/10.1007/978-3-319-91734-4_2