DocumentCode
639427
Title
Can a Fully Unconstrained Imaging Model Be Applied Effectively to Central Cameras?
Author
Bergamasco, Filippo ; Albarelli, Andrea ; Rodola, Emanuele ; Torsello, Andrea
Author_Institution
Dipt. di Sci. Ambientali, Inf. e Statistica, Univ. Ca´ Foscari Venezia, Venice, Italy
fYear
2013
fDate
23-28 June 2013
Firstpage
1391
Lastpage
1398
Abstract
Traditional camera models are often the result of a compromise between the ability to account for non-linearities in the image formation model and the need for a feasible number of degrees of freedom in the estimation process. These considerations led to the definition of several ad hoc models that best adapt to different imaging devices, ranging from pinhole cameras with no radial distortion to the more complex catadioptric or polydioptric optics. In this paper we propose the use of an unconstrained model even in standard central camera settings dominated by the pinhole model, and introduce a novel calibration approach that can deal effectively with the huge number of free parameters associated with it, resulting in a higher precision calibration than what is possible with the standard pinhole model with correction for radial distortion. This effectively extends the use of general models to settings that traditionally have been ruled by parametric approaches out of practical considerations. The benefit of such an unconstrained model to quasi-pinhole central cameras is supported by an extensive experimental validation.
Keywords
calibration; cameras; image processing; ad hoc models; fully unconstrained imaging model; image formation model; imaging devices; novel calibration approach; quasi-pinhole central camera model; radial distortion; standard central camera settings; Calibration; Cameras; Computational modeling; Estimation; Mathematical model; Three-dimensional displays; Camera Calibration; General Camera Model; Raxels;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on
Conference_Location
Portland, OR
ISSN
1063-6919
Type
conf
DOI
10.1109/CVPR.2013.183
Filename
6619027
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