2010. 2. 26. 00:07
Computer Vision
Optimal Grid Pattern for Automated Camera Calibration Using Cross Ratio
Chikara MATSUNAGA Yasushi KANAZAWA Kenichi KANATANI
Publication IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences Vol.E83-A No.10 pp.1921-1928
Publication Date: 2000/10/20
Online ISSN:
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section on Information Theory and Its Applications)
Category: Image Processing
Keyword: cross ratio, Markov process, error analysis, reliability evaluation, virtual studio,
Full Text:
출처: http://www.suri.it.okayama-u.ac.jp/~kanatani/data/ejournal.html
MVA2000 IAPR Workshop on Machine Vision Applications, Nov. 28-30,2000, The University of Tokyo, Japan
13-28
Optimal Grid Pattern for Automated Matching Using Cross Ratio
Chikara Matsunaga (Broadcast Division, FOR-A Co. Ltd.)
Kenichi Kanatanit (Department of Computer Science, Gunma University)
Kenichi Kanatani 金谷健一 http://www.suri.it.okayama-u.ac.jp/%7Ekanatani/
Yasushi Kanazawa 金澤靖 http://www.img.tutkie.tut.ac.jp/~kanazawa/
IEICE (The Institute of Electronics Information and Communication Engineers) http://www.ieice.org
IAPR (International Association of Pattern Recognition) http://www.iapr.org
IAPR - Machine Vision & Applications
Summary:
With a view to virtual studio applications, we design an optimal grid pattern such that the observed image of a small portion of it can be matched to its corresponding position in the pattern easily. The grid shape is so determined that the cross ratio of adjacent intervals is different everywhere. The cross ratios are generated by an optimal Markov process that maximizes the accuracy of matching. We test our camera calibration system using the resulting grid pattern in a realistic setting and show that the performance is greatly improved by applying techniques derived from the designed properties of the pattern.
=> "simultaneous calibration" by placing an easily distinguishable planar pattern in the scene
To find a sequence of cross ratios such that the sequence of numbers is a homogeneous increasing with the average interval being 1 and the minimum width as specified.
=> To generate the sequence of cross ratios stochastically, according to a probability distribution defined in such a way that the resulting sequence of numbers has the desired properties
=> able to optimize the probability distribution so that the matching performance is maximized by analyzing the statistical properties of image noise
Chikara MATSUNAGA Yasushi KANAZAWA Kenichi KANATANI
Publication IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences Vol.E83-A No.10 pp.1921-1928
Publication Date: 2000/10/20
Online ISSN:
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section on Information Theory and Its Applications)
Category: Image Processing
Keyword: cross ratio, Markov process, error analysis, reliability evaluation, virtual studio,
Full Text:
출처: http://www.suri.it.okayama-u.ac.jp/~kanatani/data/ejournal.html
chikaraMatsunaga_2000ieice.pdfMVA2000 IAPR Workshop on Machine Vision Applications, Nov. 28-30,2000, The University of Tokyo, Japan
13-28
Optimal Grid Pattern for Automated Matching Using Cross Ratio
Chikara Matsunaga (Broadcast Division, FOR-A Co. Ltd.)
Kenichi Kanatanit (Department of Computer Science, Gunma University)
Kenichi Kanatani 金谷健一 http://www.suri.it.okayama-u.ac.jp/%7Ekanatani/
Yasushi Kanazawa 金澤靖 http://www.img.tutkie.tut.ac.jp/~kanazawa/
IEICE (The Institute of Electronics Information and Communication Engineers) http://www.ieice.org
IAPR (International Association of Pattern Recognition) http://www.iapr.org
IAPR - Machine Vision & Applications
Summary:
With a view to virtual studio applications, we design an optimal grid pattern such that the observed image of a small portion of it can be matched to its corresponding position in the pattern easily. The grid shape is so determined that the cross ratio of adjacent intervals is different everywhere. The cross ratios are generated by an optimal Markov process that maximizes the accuracy of matching. We test our camera calibration system using the resulting grid pattern in a realistic setting and show that the performance is greatly improved by applying techniques derived from the designed properties of the pattern.
Camera calibration is a first step in all vision and media applications.> pre-calibration (Tsai) vs. self-calibration (Pollefeys)
=> "simultaneous calibration" by placing an easily distinguishable planar pattern in the scene
Introducing a statistic model of image noise, we generate the grid intervals by an optimal Markov process that maximizes the accuracy of matching.: The pattern is theoretically designed by statistical analysis
If the cross rations are given, the sequence is determined as follows.
To find a sequence of cross ratios such that the sequence of numbers is a homogeneous increasing with the average interval being 1 and the minimum width as specified.
=> To generate the sequence of cross ratios stochastically, according to a probability distribution defined in such a way that the resulting sequence of numbers has the desired properties
=> able to optimize the probability distribution so that the matching performance is maximized by analyzing the statistical properties of image noise
출처: C. Matsunaga, Y. Kanazawa, and K. Kanatani, Optimal grid pattern for automated camera calibration using cross ratio , IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, Vol. E83-A, No. 10, pp. 1921--1928, 2000. 중 1926쪽 Fig.8 4배 확대 캡처
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Ehnes, J., Hirota, K., and Hirose, M. 2004.