3D Reconstruction Quality Analysis and Its Acceleration on GPU Clusters

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F16%3APU121643" target="_blank" >RIV/00216305:26230/16:PU121643 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/EUSIPCO.2016.7760420" target="_blank" >http://dx.doi.org/10.1109/EUSIPCO.2016.7760420</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/EUSIPCO.2016.7760420" target="_blank" >10.1109/EUSIPCO.2016.7760420</a>

Jazyk výsledku

angličtina

Název v původním jazyce

3D Reconstruction Quality Analysis and Its Acceleration on GPU Clusters

Popis výsledku v původním jazyce

3D reconstruction has a wide variety of applications in computer graphics, robotics or digital cinema production, among others. With the rapid increase in computing power, it has become more feasible for the reconstruction algorithms to run online, even on mobile devices. Maximum likelihood estimation (MLE) is the adopted technique to deal with the sensor uncertainty. Most of the existing 3D reconstruction frameworks only recover the mean of the reconstructed geometry. Recovering also the variance is highly computationally intensive and is seldom performed. However, variance is the natural choice of estimate quality indicator. In this paper, the associated costs are analyzed and efficient but exact solutions to calculating partial matrix inverses are proposed, which apply to any general problem with many mutually independent variables. Speedups exceeding an order of magnitude are reported.

Název v anglickém jazyce

3D Reconstruction Quality Analysis and Its Acceleration on GPU Clusters

Popis výsledku anglicky

3D reconstruction has a wide variety of applications in computer graphics, robotics or digital cinema production, among others. With the rapid increase in computing power, it has become more feasible for the reconstruction algorithms to run online, even on mobile devices. Maximum likelihood estimation (MLE) is the adopted technique to deal with the sensor uncertainty. Most of the existing 3D reconstruction frameworks only recover the mean of the reconstructed geometry. Recovering also the variance is highly computationally intensive and is seldom performed. However, variance is the natural choice of estimate quality indicator. In this paper, the associated costs are analyzed and efficient but exact solutions to calculating partial matrix inverses are proposed, which apply to any general problem with many mutually independent variables. Speedups exceeding an order of magnitude are reported.

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

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of European Signal Processing Conference 2016

ISBN

978-0-9928626-6-4

ISSN

—

e-ISSN

—

Počet stran výsledku

8

Strana od-do

1-8

Název nakladatele

Institute of Electrical and Electronics Engineers

Místo vydání

Budapest

Místo konání akce

Budapest

Datum konání akce

29. 8. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000391891900475