On the Two-View Geometry of Unsynchronized Cameras
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F17%3A00315310" target="_blank" >RIV/68407700:21230/17:00315310 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21730/17:00315310
Result on the web
<a href="http://dx.doi.org/10.1109/CVPR.2017.593" target="_blank" >http://dx.doi.org/10.1109/CVPR.2017.593</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/CVPR.2017.593" target="_blank" >10.1109/CVPR.2017.593</a>
Alternative languages
Result language
angličtina
Original language name
On the Two-View Geometry of Unsynchronized Cameras
Original language description
We present new methods of simultaneously estimating camera geometry and time shift from video sequences from multiple unsynchronized cameras. Algorithms for simultaneous computation of a fundamental matrix or a homography with unknown time shift between images are developed. Our methods use minimal correspondence sets (eight for fundamental matrix and four and a half for homography) and therefore are suitable for robust estimation using RANSAC. Furthermore, we present an iterative algorithm that extends the applicability on sequences which are significantly unsynchronized, finding the correct time shift up to several seconds. We evaluated the methods on synthetic and wide range of real world datasets and the results show a broad applicability to the problem of camera synchronization.
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/GBP103%2F12%2FG084" target="_blank" >GBP103/12/G084: Center for Large Scale Multi-modal Data Interpretation</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
CVPR 2017: Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition
ISBN
978-1-5386-0457-1
ISSN
1063-6919
e-ISSN
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Number of pages
10
Pages from-to
5593-5602
Publisher name
IEEE Computer Society Press
Place of publication
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Event location
Honolulu
Event date
Jul 21, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000418371405072