Minimal solutions for panoramic stitching given gravity prior
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F21%3A00354635" target="_blank" >RIV/68407700:21230/21:00354635 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/ICCV48922.2021.00553" target="_blank" >https://doi.org/10.1109/ICCV48922.2021.00553</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICCV48922.2021.00553" target="_blank" >10.1109/ICCV48922.2021.00553</a>
Alternative languages
Result language
angličtina
Original language name
Minimal solutions for panoramic stitching given gravity prior
Original language description
When capturing panoramas, people tend to align their cameras with the vertical axis, i.e., the direction of gravity. Moreover, modern devices, e.g. smartphones and tablets, are equipped with an IMU (Inertial Measurement Unit) that can measure the gravity vector accurately. Using this prior, the y-axes of the cameras can be aligned or assumed to be already aligned, reducing the relative orientation to 1-DOF (degree of freedom). Exploiting this assumption, we propose new minimal solutions to panoramic stitching of images taken by cameras with coinciding optical centers, i.e. undergoing pure rotation. We consider six practical camera configurations, from fully calibrated ones up to a camera with unknown fixed or varying focal length and with or without radial distortion. The solvers are tested both on synthetic scenes, on more than 500k real image pairs from the Sun360 dataset, and from scenes captured by us using two smartphones equipped with IMUs. The new solvers have similar or better accuracy than the state-of-the-art ones and outperform them in terms of processing time.
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/LL1901" target="_blank" >LL1901: Generalized Image Retrieval and Relation Discovery</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
ICCV2021: Proceedings of the International Conference on Computer Vision
ISBN
978-1-6654-2812-5
ISSN
1550-5499
e-ISSN
2380-7504
Number of pages
10
Pages from-to
5579-5588
Publisher name
IEEE
Place of publication
Piscataway
Event location
Montreal
Event date
Oct 11, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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