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Robust Method for Recovering Sign of Gaussian Curvature from Multiple Shading Images
https://nitech.repo.nii.ac.jp/records/5021
https://nitech.repo.nii.ac.jp/records/50216d89ec1a-eb07-4aed-9bab-93005795b6c1
名前 / ファイル | ライセンス | アクション |
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本文_fulltext (3.9 MB)
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Copyright(c)2001 IEICE http://search.ieice.org/index.html
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Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2013-06-25 | |||||
タイトル | ||||||
言語 | en | |||||
タイトル | Robust Method for Recovering Sign of Gaussian Curvature from Multiple Shading Images | |||||
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 |
Fukui, Shinji
× Fukui, Shinji× Iwahori, Yuji× Woodham, Robert J.× Funahashi, Kenji× Iwata, Akira |
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著者別名 | ||||||
姓名 | 舟橋, 健司 | |||||
著者別名 | ||||||
姓名 | 岩田, 彰 | |||||
書誌情報 |
IEICE transactions on information and systems 巻 E84-D, 号 12, p. 1633-1641, 発行日 2001-12-01 |
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出版者 | ||||||
出版者 | Institute of Electronics, Information and Communication Engineers | |||||
ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 09168532 | |||||
書誌レコードID(NCID) | ||||||
収録物識別子タイプ | NCID | |||||
収録物識別子 | AA10826272 | |||||
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 | |||||
内容記述 | ||||||
内容記述タイプ | Other | |||||
内容記述 | This paper proposes a new method to recover the sign of local Gaussian curvature from multiple (more than three) shading images. The information required to recover the sign of Gaussian curvature is obtained by applying Principal Components Analysis (PCA) to the normalized irradiance measurements. The sign of the Gaussian curvature is recovered based on the relative orientation of measurements obtained on a local five point test pattern to those in the 2-D subspace called the eigen plane. Using multiple shading images gives a more accurate and robust result and minimizes the effect of shadows by allowing a larger area of the visible surface to be analyzed compared to methods using only three shading images. Furthermore, it allows the method to be applied to specular surfaces. Since PCA removes linear correlation among images, the method can produce results of high quality even when the light source directions are not widely dispersed. | |||||
フォーマット | ||||||
内容記述タイプ | Other | |||||
内容記述 | application/pdf |