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Automatic moving object extraction using X-means clustering
http://hdl.handle.net/2297/27072
http://hdl.handle.net/2297/270722f170353-d360-4553-96bd-bddcf51f2d80
名前 / ファイル | ライセンス | アクション |
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TE-PR-IMAMURA-K-246.pdf (208.1 kB)
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Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2017-10-03 | |||||
タイトル | ||||||
タイトル | Automatic moving object extraction using X-means clustering | |||||
言語 | ||||||
言語 | eng | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
資源タイプ | journal article | |||||
著者 |
Imamura, Kousuke
× Imamura, Kousuke× Kubo, Naoki× Hashimoto, Hideo |
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提供者所属 | ||||||
内容記述タイプ | Other | |||||
内容記述 | 金沢大学理工研究域電子情報学系 | |||||
書誌情報 |
28th Picture Coding Symposium, PCS 2010 号 5702477, p. 246-249, 発行日 2010-01-01 |
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DOI | ||||||
関連タイプ | isIdenticalTo | |||||
識別子タイプ | DOI | |||||
関連識別子 | 10.1109/PCS.2010.5702477 | |||||
出版者 | ||||||
出版者 | IEEE = Institute of Electrical and Electronics Engineers | |||||
抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | The present paper proposes an automatic extraction technique of moving objects using x-means clustering. The proposed technique is an extended k-means clustering and can determine the optimal number of clusters based on the Bayesian Information Criterion(BIC). In the proposed method, the feature points are extracted from a current frame, and x-means clustering classifies the feature points based on their estimated affine motion parameters. A label is assigned to the segmented region, which is obtained by morphological watershed, by voting for the feature point cluster in each region. The labeling result represents the moving object extraction. Experimental results reveal that the proposed method provides extraction results with the suitable object number. © 2010 IEEE. | |||||
著者版フラグ | ||||||
出版タイプ | VoR | |||||
出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 |