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A Modified RANSAC mechanism:Multiple models extraction algorithm
https://ipsj.ixsq.nii.ac.jp/records/52156
https://ipsj.ixsq.nii.ac.jp/records/52156d564c8ba-f84e-4da4-b423-29da63814141
名前 / ファイル | ライセンス | アクション |
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Copyright (c) 2006 by the Information Processing Society of Japan
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オープンアクセス |
Item type | SIG Technical Reports(1) | |||||||
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公開日 | 2006-09-09 | |||||||
タイトル | ||||||||
タイトル | A Modified RANSAC mechanism:Multiple models extraction algorithm | |||||||
タイトル | ||||||||
言語 | en | |||||||
タイトル | A Modified RANSAC mechanism:Multiple models extraction algorithm | |||||||
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_18gh | |||||||
資源タイプ | technical report | |||||||
著者所属 | ||||||||
Waseda University Graduate School of Global Information and Telecommunication | ||||||||
著者所属 | ||||||||
Waseda University Graduate School of Global Information and Telecommunication | ||||||||
著者所属(英) | ||||||||
en | ||||||||
Waseda University, Graduate School of Global Information and Telecommunication | ||||||||
著者所属(英) | ||||||||
en | ||||||||
Waseda University, Graduate School of Global Information and Telecommunication | ||||||||
著者名 |
Yingdi, Xie
× Yingdi, Xie
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著者名(英) |
Yingdi, Xie
× Yingdi, Xie
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論文抄録 | ||||||||
内容記述タイプ | Other | |||||||
内容記述 | As one of the most frequently used regression methods RANSAC is advanced in its effectiveness and efficiency but RANSAC cannot extract multiple models due to its exclusivity. To extract multiple models this paper proposes a new regression method which is a modified version of RANSAC. To fit a model to data points a labeling process classifies each data point into proper inlier quasi-inlier or outlier. The model is obtained from the proper and quasi inliers. After eliminating the proper inliers another model fitting is performed. These operations are repeated till no more model is fitted. The effectiveness of the proposed method is shown by experiments on extracting multiple lines from images. | |||||||
論文抄録(英) | ||||||||
内容記述タイプ | Other | |||||||
内容記述 | As one of the most frequently used regression methods, RANSAC is advanced in its effectiveness and efficiency, but RANSAC cannot extract multiple models due to its exclusivity. To extract multiple models, this paper proposes a new regression method, which is a modified version of RANSAC. To fit a model to data points, a labeling process classifies each data point into proper inlier, quasi-inlier or outlier. The model is obtained from the proper and quasi inliers. After eliminating the proper inliers, another model fitting is performed. These operations are repeated till no more model is fitted. The effectiveness of the proposed method is shown by experiments on extracting multiple lines from images. | |||||||
書誌レコードID | ||||||||
収録物識別子タイプ | NCID | |||||||
収録物識別子 | AA11131797 | |||||||
書誌情報 |
情報処理学会研究報告コンピュータビジョンとイメージメディア(CVIM) 巻 2006, 号 93(2006-CVIM-155), p. 159-166, 発行日 2006-09-09 |
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Notice | ||||||||
SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc. | ||||||||
出版者 | ||||||||
言語 | ja | |||||||
出版者 | 情報処理学会 |