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ID 34797
本文ファイル
著者
Matsukawa, Tetsu
キーワード
Image recognition
Higher-order local autocorrelation feature
Bag-of-features
Posterior probability image
NDC
情報科学
抄録(英)
This paper presents a novel image representation method for generic object recognition by using higher-order local autocorrelations on posterior probability images. The proposed method is an extension of the bag-of-features approach to posterior probability images. The standard bag-of-features approach is approximately thought of as a method that classifies an image to a category whose sum of posterior probabilities on a posterior probability image is maximum. However, by using local autocorrelations of posterior probability images, the proposed method extracts richer information than the standard bag-of-features. Experimental results reveal that the proposed method exhibits higher classification performances than the standard bag-of-features method.
掲載誌名
Pattern Recognition
45巻
2号
開始ページ
707
終了ページ
719
出版年月日
2012
出版者
Elsevier Science BV
ISSN
0031-3203
NCID
出版者DOI
言語
英語
NII資源タイプ
学術雑誌論文
広大資料タイプ
学術雑誌論文
DCMIタイプ
text
フォーマット
application/pdf
著者版フラグ
author
権利情報
This is a preprint of an article submitted for consideration in Pattern Recognition (c) 2012 Elsevier B.V. ; Pattern Recognition is available online at ScienceDirect with the open URL of your article;
関連情報URL
部局名
工学研究科