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ID 46969
フルテキストURL
著者
Kanatani, Kenichi Department of Information Technology, Okayama University
抄録
In order to facilitate smooth communications with researchers in other fields including statistics, this paper investigates the meaning of "statistical methods" for geometric inference based on image feature points, We point out that statistical analysis does not make sense unless the underlying "statistical ensemble" is clearly defined. We trace back the origin of feature uncertainty to image processing operations for computer vision in general and discuss the implications of asymptotic analysis for performance evaluation in reference to "geometric fitting", "geometric model selection", the "geometric AIC", and the "geometric MDL". Referring to such statistical concepts as "nuisance parameters", the "Neyman-Scott problem", and "semiparametric models", we point out that simulation experiments for performance evaluation will lose meaning without carefully considering the assumptions involved and intended applications.
発行日
2002-11
出版物タイトル
Memoirs of the Faculty of Engineering, Okayama University
37巻
1号
出版者
Faculty of Engineering, Okayama University
開始ページ
15
終了ページ
23
ISSN
0475-0071
NCID
AA10699856
資料タイプ
紀要論文
言語
English
論文のバージョン
publisher
査読
無し
Eprints Journal Name
mfe