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ID 19955
Eprint ID
19955
FullText URL
Author
Sugaya Yasuyuki
Abstract
A new numerical scheme is presented for computing strict maximum likelihood (ML) of geometric fitting problems having an implicit constraint. Our approach is orthogonal projection of observations onto a parameterized surface defined by the constraint. Assuming a linearly separable nonlinear constraint, we show that a theoretically global solution can be obtained by iterative Sampson error minimization. Our approach is illustrated by ellipse fitting and fundamental matrix computation. Our method also encompasses optimal correction, computing, e.g., perpendiculars to an ellipse and triangulating stereo images. A detailed discussion is given to technical and practical issues about our approach.
Published Date
2010-01
Publication Title
Memoirs of the Faculty of Engineering, Okayama University
Publication Title Alternative
岡山大学工学部紀要
Volume
volume44
Publisher
Faculty of Engineering, Okayama University
Publisher Alternative
岡山大学工学部
Start Page
13
End Page
23
ISSN
1349-6115
NCID
AA12014085
Content Type
Departmental Bulletin Paper
language
英語
File Version
publisher
Refereed
False
Eprints Journal Name
mfe