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Paper Abstract and Keywords
Presentation 2005-03-14 15:45
[Invited Talk] Geometric Inference from Images and Model Selection
Kenichi Kanatani (Okayama Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) Model selection is to infer the law that underlies observed sensor
data. Once the law is known, the next step is to optimally estimate
the unknown parameters contained in the governing equation, which has
been well studied by statisticians. In contrast, model selection is
in a sense a transcendental problem: Although many principals have
been proposed in the past, there is no logical ground to assert that
one is better than others, and the choice is left to the user. The
purpose of this lecture is to show how Akaike's AIC and Rissanen's
MDL, the two selection criteria best known in statistics, can be
applied to image processing and computer vision problems. First, it
is pointed out that Akaike's AIC and Rissanen's MDL cannot be applied
to geometric inference in their original forms. It is shown that if
we go back to their starting principles and modify their derivations
so that they fit into the framework of image processing and computer
vision, we obtain the geometric AIC and the geometric MDL that the
author proposed. In this lecture, we describe their essential
distinction from Akaike's AIC and Rissanen's MDL in intuitive terms.
Using easy-to-understand real image examples, we demonstrate how
extensive their applications to geometric inference in image
processing and computer vision problems are.
Keyword (in Japanese) (See Japanese page) 
(in English) geometric fitting / model selection / AIC / MDL / image processing / computer vision / /  
Reference Info. IEICE Tech. Rep., vol. 104, no. 718, SIP2004-138, pp. 77-82, March 2005.
Paper # SIP2004-138 
Date of Issue 2005-03-07 (CAS, SIP, CS) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380

Conference Information
Committee CS CAS SIP  
Conference Date 2005-03-14 - 2005-03-15 
Place (in Japanese) (See Japanese page) 
Place (in English) Okayama Prefectural University 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Network processors, signal processing for communications, coding theory, etc. 
Paper Information
Registration To SIP 
Conference Code 2005-03-CS-CAS-SIP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Geometric Inference from Images and Model Selection 
Sub Title (in English)  
Keyword(1) geometric fitting  
Keyword(2) model selection  
Keyword(3) AIC  
Keyword(4) MDL  
Keyword(5) image processing  
Keyword(6) computer vision  
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Keyword(8)  
1st Author's Name Kenichi Kanatani  
1st Author's Affiliation Okayama University (Okayama Univ.)
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Speaker
Date Time 2005-03-14 15:45:00 
Presentation Time 70 
Registration for SIP 
Paper # IEICE-CAS2004-95,IEICE-SIP2004-138,IEICE-CS2004-231 
Volume (vol) IEICE-104 
Number (no) no.716(CAS), no.718(SIP), no.720(CS) 
Page pp.77-82 
#Pages IEICE-6 
Date of Issue IEICE-CAS-2005-03-07,IEICE-SIP-2005-03-07,IEICE-CS-2005-03-07 


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