Presentation 2007-09-03
Maximum Likelihood Estimation of the Fundamental Matrix in the Presence of Large Noise
Kenichi Kanatani, Yasuyuki Sugaya,
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Abstract(in English) Many methods have been proposed for computing the fundamental matrix from noisy point correspondences over two images. This paper presents a new method for computing exact maximum likelihood in the image plane for high noise level. Unlike existing such methods, our method iteratively applies a simple method for low noise level, greatly simplifies the computation. Using simulated and real images, we show that no significant accuracy improvement is observed as compared with the low noise level method, concluding that the low noise level method is sufficient for practical applications.
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Paper # PRMU2007-56,HIP2007-65
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Committee HIP
Conference Date 2007/8/27(1days)
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Language JPN
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Title (in English) Maximum Likelihood Estimation of the Fundamental Matrix in the Presence of Large Noise
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1st Author's Name Kenichi Kanatani
1st Author's Affiliation Department of Computer Science, Okayama University()
2nd Author's Name Yasuyuki Sugaya
2nd Author's Affiliation Department of Information and Computer Sciences, Toyohashi University of Technology
Date 2007-09-03
Paper # PRMU2007-56,HIP2007-65
Volume (vol) vol.107
Number (no) 207
Page pp.pp.-
#Pages 8
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