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Image categorization by a classifier based on probabilistic topic model
http://hdl.handle.net/10091/12019
http://hdl.handle.net/10091/120194b71ab6c-7fa9-4f92-8dff-fb01a1edccfb
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
icpr2008_final_font.pdf (405.1 kB)
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| Item type | 会議発表論文 / Conference Paper(1) | |||||||||
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| 公開日 | 2011-03-10 | |||||||||
| タイトル | ||||||||||
| タイトル | Image categorization by a classifier based on probabilistic topic model | |||||||||
| 言語 | en | |||||||||
| 言語 | ||||||||||
| 言語 | eng | |||||||||
| 資源タイプ | ||||||||||
| 資源 | http://purl.org/coar/resource_type/c_5794 | |||||||||
| タイプ | conference paper | |||||||||
| 著者 |
YAMAGUCHI, Takuma
× YAMAGUCHI, Takuma
× MARUYAMA, Minoru
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| 信州大学研究者総覧へのリンク | ||||||||||
| 氏名 | MARUYAMA, Minoru | |||||||||
| URL | http://soar-rd.shinshu-u.ac.jp/profile/ja.WCnCbpkh.html | |||||||||
| 出版者 | ||||||||||
| 出版者 | International Conference on Pattern Recognition | |||||||||
| 引用 | ||||||||||
| 内容記述タイプ | Other | |||||||||
| 内容記述 | International Conference on Pattern Recognition: 1-4 2008 | |||||||||
| 書誌情報 |
p. 1-4, 発行日 2008 |
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| 抄録 | ||||||||||
| 内容記述タイプ | Abstract | |||||||||
| 内容記述 | With rapid increase of number of accessible images and videos, ability to recognize visual information is getting more and more important for content-based information retrieval. Recently, probabilistic topic models, which were originally developed for text analysis, have been used for image categorization successfully. Usually, topics which represent contents of an image is detected based on the underlying probabilistic model, then image categorization is carried out using topic distribution as the input feature. Typical method is to use k-nearest neighbor classifier based on L2-distance after topic discovery. In the method, topic distribution is just treated as a feature point. In this paper, we propose a categorization method based on more natural use of the topic distribution, which is derived by using pLSA model. Categorization is carried out by estimating conditional probability p(categoryjdata). We present two types of image categorization tasks, scene classification and document image segmentation, and show the proposed method performs very well. In addition, we also examine the performance of the proposed method under the situation where only the limited number of labeled examples are available. We show our method can perform quite well even in the circumstances. | |||||||||
| 資源タイプ（コンテンツの種類） | ||||||||||
| 内容記述タイプ | Other | |||||||||
| 内容記述 | Article | |||||||||
| 出版タイプ | ||||||||||
| 出版タイプ | VoR | |||||||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||||
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Cite as
YAMAGUCHI, Takuma, MARUYAMA, Minoru, 2008, Image categorization by a classifier based on probabilistic topic model: International Conference on Pattern Recognition, 1–4 p.
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