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ID 30017
フルテキストURL
著者
Kanatani, Kenichi Okayama University Kaken ID publons researchmap
抄録

We first investigate the meaning of "statistical methods" for geometric inference based on image feature points. Tracing back the origin of feature uncertainty to image processing operations, we discuss the implications of asymptotic analysis in reference to "geometric fitting" and "geometric model selection" and point out that a correspondence exists between the standard statistical analysis and the geometric inference problem. Then, we derive the "geometric AIC" and the "geometric MDL" as counterparts of Akaike's AIC and Rissanen's MDL. We show by experiments that the two criteria have contrasting characteristics in detecting degeneracy.

キーワード
65
Index Terms- Statistical method
asymptotic evaluation
feature point extraction
geometric AIC
geometric
MDL.
備考
Digital Object Identifier: 10.1109/TPAMI.2004.93
Published with permission from the copyright holder.this is the institute's copy, as published in Pattern Analysis and Machine Intelligence, IEEE Transactions on, Oct. 2004, Volume: 26, Issue: 10, Pages 1307-1319.
Publisher URL:http://dx.doi.org/10.1109/TPAMI.2004.93
Copyright © 2004 IEEE. All rights reserved.
発行日
2004-10
出版物タイトル
Pattern Analysis and Machine Intelligence
開始ページ
1307
終了ページ
1319
資料タイプ
学術雑誌論文
言語
英語
査読
有り
DOI
Submission Path
industrial_engineering/111