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

Result code in 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>

Result on the web

<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>

Result language

angličtina

Original language name

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

Original language description

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.

Czech name

—

Czech description

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Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

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

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2017

Confidentiality

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

Article name in the collection

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

ISBN

978-1-5386-2682-5

ISSN

—

e-ISSN

2153-0866

Number of pages

8

Pages from-to

4394-4401

Publisher name

IEEE

Place of publication

Piscataway

Event location

Vancouver

Event date

Sep 24, 2017

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000426978204039