DocumentCode :
848635
Title :
High-Accuracy and Robust Localization of Large Control Markers for Geometric Camera Calibration
Author :
Douxchamps, Damien ; Chihara, Kunihiro
Author_Institution :
Image Process. Lab., Nara Inst. of Sci. & Technol., Ikoma
Volume :
31
Issue :
2
fYear :
2009
Firstpage :
376
Lastpage :
383
Abstract :
Accurate measurement of the position of features in an image is subject to a fundamental compromise: The features must be both small, to limit the effect of nonlinear distortions, and large, to limit the effect of noise and discretization. This constrains both the accuracy and the robustness of image measurements, which play an important role in geometric camera calibration as well as in all subsequent measurements based on that calibration. In this paper, we present a new geometric camera calibration technique that exploits the complete camera model during the localization of control markers, thereby abolishing the marker size compromise. Large markers allow a dense pattern to be used instead of a simple disc, resulting in a significant increase in accuracy and robustness. When highly planar markers are used, geometric camera calibration based on synthetic images leads to true errors of 0.002 pixels, even in the presence of artifacts such as noise, illumination gradients, compression, blurring, and limited dynamic range. The camera parameters are also accurately recovered, even for complex camera models.
Keywords :
cameras; feature extraction; geometry; complex camera models; control markers; geometric camera calibration; high-accuracy-robust localization; image measurements; nonlinear distortions; subsequent measurements; synthetic images; Camera calibration; Imaging geometry; high resolution; image measurement; imaging geometry; noise; ray tracing; subpixel.; Algorithms; Artifacts; Artificial Intelligence; Calibration; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Pattern Recognition, Automated; Photogrammetry; Reproducibility of Results; Sensitivity and Specificity;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/TPAMI.2008.214
Filename :
4609385
Link To Document :
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