Efficient Structure from Motion by Graph Optimization

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F10%3A00175511" target="_blank" >RIV/68407700:21230/10:00175511 - isvavai.cz</a>

Výsledek na webu

—

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Efficient Structure from Motion by Graph Optimization

Popis výsledku v původním jazyce

We present an efficient structure from motion algorithm that can deal with large image collections in a fraction of time and effort of previous approaches while providing comparable quality of the scene and camera reconstruction. First, we employ fast image indexing using large image vocabularies to measure visual overlap of images without running actual image matching. Then, we select a small subset from the set of input images by computing its approximate minimal connected dominating set by a fast polynomial algorithm. Finally, we use task prioritization to avoid spending too much time in a few difficult matching problems instead of exploring other easier options. Thus we avoid wasting time on image pairs with low chance of success and avoid matchingof highly redundant images of landmarks. We present results for several challenging sets of thousands of perspective as well as omnidirectional images.

Název v anglickém jazyce

Efficient Structure from Motion by Graph Optimization

Popis výsledku anglicky

We present an efficient structure from motion algorithm that can deal with large image collections in a fraction of time and effort of previous approaches while providing comparable quality of the scene and camera reconstruction. First, we employ fast image indexing using large image vocabularies to measure visual overlap of images without running actual image matching. Then, we select a small subset from the set of input images by computing its approximate minimal connected dominating set by a fast polynomial algorithm. Finally, we use task prioritization to avoid spending too much time in a few difficult matching problems instead of exploring other easier options. Thus we avoid wasting time on image pairs with low chance of success and avoid matchingof highly redundant images of landmarks. We present results for several challenging sets of thousands of perspective as well as omnidirectional images.

Druh

D - Stať ve sborníku

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

—

Projekt

<a href="/cs/project/7E10047" target="_blank" >7E10047: Humanoids with auditory and visual abilities in populated spaces</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)<br>R - Projekt Ramcoveho programu EK

Rok uplatnění

2010

Kód důvěrnosti údajů

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

Název statě ve sborníku

Computer Vision - ECCV 2010, 11th European Conference on Computer Vision, Proceedings, Part II

ISBN

978-3-642-15551-2

ISSN

0302-9743

e-ISSN

—

Počet stran výsledku

14

Strana od-do

—

Název nakladatele

Springer

Místo vydání

Berlin

Místo konání akce

Heraklion

Datum konání akce

5. 9. 2010

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000286164000008