Inertial-Based Scale Estimation for Structure from Motion on Mobile Devices

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F17%3A00315729" target="_blank" >RIV/68407700:21230/17:00315729 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/IROS.2017.8206303" target="_blank" >http://dx.doi.org/10.1109/IROS.2017.8206303</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/IROS.2017.8206303" target="_blank" >10.1109/IROS.2017.8206303</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Inertial-Based Scale Estimation for Structure from Motion on Mobile Devices

Popis výsledku v původním jazyce

Structure from motion algorithms have an inherent limitation that the reconstruction can only be determined up to the unknown scale factor. Modern mobile devices are equipped with an inertial measurement unit (IMU), which can be used for estimating the scale of the reconstruction. We propose a method that recovers the metric scale given inertial measurements and camera poses. In the process, we also perform a temporal and spatial alignment of the camera and the IMU. Therefore, our solution can be easily combined with any existing visual reconstruction software. The method can cope with noisy camera pose estimates, typically caused by motion blur or rolling shutter artifacts, via utilizing a Rauch-Tung-Striebel (RTS) smoother. Furthermore, the scale estimation is performed in the frequency domain, which provides more robustness to inaccurate sensor time stamps and noisy IMU samples than the previously used time domain representation. In contrast to previous methods, our approach has no parame- ters that need to be tuned for achieving a good performance. In the experiments, we show that the algorithm outperforms the state-of-the-art in both accuracy and convergence speed of the scale estimate. The accuracy of the scale is around 1% from the ground truth depending on the recording. We also demonstrate that our method can improve the scale accuracy of the Project Tango’s build-in motion tracking.

Název v anglickém jazyce

Inertial-Based Scale Estimation for Structure from Motion on Mobile Devices

Popis výsledku anglicky

Structure from motion algorithms have an inherent limitation that the reconstruction can only be determined up to the unknown scale factor. Modern mobile devices are equipped with an inertial measurement unit (IMU), which can be used for estimating the scale of the reconstruction. We propose a method that recovers the metric scale given inertial measurements and camera poses. In the process, we also perform a temporal and spatial alignment of the camera and the IMU. Therefore, our solution can be easily combined with any existing visual reconstruction software. The method can cope with noisy camera pose estimates, typically caused by motion blur or rolling shutter artifacts, via utilizing a Rauch-Tung-Striebel (RTS) smoother. Furthermore, the scale estimation is performed in the frequency domain, which provides more robustness to inaccurate sensor time stamps and noisy IMU samples than the previously used time domain representation. In contrast to previous methods, our approach has no parame- ters that need to be tuned for achieving a good performance. In the experiments, we show that the algorithm outperforms the state-of-the-art in both accuracy and convergence speed of the scale estimate. The accuracy of the scale is around 1% from the ground truth depending on the recording. We also demonstrate that our method can improve the scale accuracy of the Project Tango’s build-in motion tracking.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Intelligent Robots and Systems (IROS), 2017 IEEE/RSJ International Conference on

ISBN

978-1-5386-2682-5

ISSN

—

e-ISSN

2153-0866

Počet stran výsledku

8

Strana od-do

4394-4401

Název nakladatele

IEEE

Místo vydání

Piscataway

Místo konání akce

Vancouver

Datum konání akce

24. 9. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000426978204039