Fast and Accurate Camera Covariance Computation for Large 3D Reconstruction
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F18%3A00326793" target="_blank" >RIV/68407700:21730/18:00326793 - isvavai.cz</a>
Result on the web
<a href="http://openaccess.thecvf.com/content_ECCV_2018/papers/Michal_Polic_Fast_and_Precise_ECCV_2018_paper.pdf" target="_blank" >http://openaccess.thecvf.com/content_ECCV_2018/papers/Michal_Polic_Fast_and_Precise_ECCV_2018_paper.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-01216-8_42" target="_blank" >10.1007/978-3-030-01216-8_42</a>
Alternative languages
Result language
angličtina
Original language name
Fast and Accurate Camera Covariance Computation for Large 3D Reconstruction
Original language description
Estimating uncertainty of camera parameters computed in Structure from Motion (SfM) is an important tool for evaluating the quality of the reconstruction and guiding the reconstruction process. Yet, the quality of the estimated parameters of large reconstructions has been rarely evaluated due to the computational challenges. We present a new algorithm which employs the sparsity of the uncertainty propagation and speeds the computation up about ten times w.r.t. previous approaches. Our computation is accurate and does not use any approximations. We can compute uncertainties of thousands of cameras in tens of seconds on a standard PC. We also demonstrate that our approach can be effectively used for reconstructions of any size by applying it to smaller sub-reconstructions.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/EF15_003%2F0000468" target="_blank" >EF15_003/0000468: Intelligent Machine Perception</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
ECCV2018: Proceedings of the European Conference on Computer Vision, Part II
ISBN
978-3-030-01215-1
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
16
Pages from-to
697-712
Publisher name
Springer International Publishing
Place of publication
Cham
Event location
Munich
Event date
Sep 8, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000594207400042