PlaneCalib: Automatic Camera Calibration by Multiple Observations of Rigid Objects on Plane
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F20%3APU138876" target="_blank" >RIV/00216305:26230/20:PU138876 - isvavai.cz</a>
Result on the web
<a href="http://www.dicta2020.org/wp-content/uploads/2020/09/58_CameraReady.pdf" target="_blank" >http://www.dicta2020.org/wp-content/uploads/2020/09/58_CameraReady.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/DICTA51227.2020.9363417" target="_blank" >10.1109/DICTA51227.2020.9363417</a>
Alternative languages
Result language
angličtina
Original language name
PlaneCalib: Automatic Camera Calibration by Multiple Observations of Rigid Objects on Plane
Original language description
In this work, we propose a novel method for automatic camera calibration, mainly for surveillance cameras. The calibration consists in observing objects on the ground plane of the scene; in our experiments, vehicles were used. However, any arbitrary rigid objects can be used instead, as verified by experiments with synthetic data. The calibration process uses convolutional neural network localisation of landmarks on the observed objects in the scene and the corresponding 3D positions of the localised landmarks - thus fine-grained classification of the detected vehicles in the image plane is done. The observation of the objects (detection, classification and landmark detection) enables to determine all typically used camera calibration parameters (focal length, rotation matrix, and translation vector). The experiments with real data show slightly better results in comparison with state-of-the-art work, however with an extreme speed-up. The calibration error decreased from 3.01 % to 2.72 % and 1223 × faster computation was achieved.
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
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2020 International Conference on Digital Image Computing: Techniques and Applications (DICTA)
ISBN
978-1-7281-9108-9
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
1-8
Publisher name
Institute of Electrical and Electronics Engineers
Place of publication
Melbourne
Event location
Melbourne
Event date
Nov 30, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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