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ICPR
2010
IEEE

Hyper Least Squares and Its Applications

13 years 11 months ago
Hyper Least Squares and Its Applications
We present a new form of least squares (LS), called “hyperLS”, for geometric problems that frequently appear in computer vision applications. Doing rigorous error analysis, we maximize the accuracy by introducing a normalization that eliminates statistical bias up to second order noise terms. Our method yields a solution comparable to maximum likelihood (ML) without iterations, even in large noise situations where ML computation fails.
Prasanna Rangarajan, Kenichi Kanatani, Hirotaka Ni
Added 07 Dec 2010
Updated 07 Dec 2010
Type Conference
Year 2010
Where ICPR
Authors Prasanna Rangarajan, Kenichi Kanatani, Hirotaka Niitsuma, Yasuyuki Sugaya
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