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Fast Projective Reconstruction: Toward Ultimate Efficiency
https://ipsj.ixsq.nii.ac.jp/records/17934
https://ipsj.ixsq.nii.ac.jp/records/17934fb09c6b7-3e73-4643-a9ac-3123120a9554
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
IPSJ-TCVIM4906009.pdf (1.0 MB)
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Copyright (c) 2008 by the Information Processing Society of Japan
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| オープンアクセス | ||
| Item type | Trans(1) | |||||||
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| 公開日 | 2008-03-15 | |||||||
| タイトル | ||||||||
| タイトル | Fast Projective Reconstruction: Toward Ultimate Efficiency | |||||||
| タイトル | ||||||||
| 言語 | en | |||||||
| タイトル | Fast Projective Reconstruction: Toward Ultimate Efficiency | |||||||
| 言語 | ||||||||
| 言語 | eng | |||||||
| キーワード | ||||||||
| 主題Scheme | Other | |||||||
| 主題 | 研究論文（推薦） | |||||||
| 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 | |||||||
| 著者所属 | ||||||||
| Okayama University | ||||||||
| 著者所属 | ||||||||
| Okayama University | ||||||||
| 著者所属(英) | ||||||||
| en | ||||||||
| Okayama University | ||||||||
| 著者所属(英) | ||||||||
| en | ||||||||
| Okayama University | ||||||||
| 著者名 |
Hanno, Ackermann
Kenichi, Kanatani
× Hanno, Ackermann Kenichi, Kanatani
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| 著者名(英) |
Hanno, Ackermann
Kenichi, Kanatani
× Hanno, Ackermann Kenichi, Kanatani
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| 論文抄録 | ||||||||
| 内容記述タイプ | Other | |||||||
| 内容記述 | We accelerate the time-consuming iterations for projective reconstruction a key component of self-calibration for computing 3-D shapes from feature point tracking over a video sequence.We first summarize the algorithms of the primal and dual methods for projective reconstruction.Then we replace the eigenvalue computation in each step by the power method. We also accelerate the power method itself. Furthermore we introduce the SOR method for accelerating the subspace fitting involved in the iterations. Using simulated and real video images we demonstrate that the computation sometimes becomes several thousand times faster. | |||||||
| 論文抄録(英) | ||||||||
| 内容記述タイプ | Other | |||||||
| 内容記述 | We accelerate the time-consuming iterations for projective reconstruction, a key component of self-calibration for computing 3-D shapes from feature point tracking over a video sequence.We first summarize the algorithms of the primal and dual methods for projective reconstruction.Then, we replace the eigenvalue computation in each step by the power method. We also accelerate the power method itself. Furthermore, we introduce the SOR method for accelerating the subspace fitting involved in the iterations. Using simulated and real video images,we demonstrate that the computation sometimes becomes several thousand times faster. | |||||||
| 書誌レコードID | ||||||||
| 収録物識別子タイプ | NCID | |||||||
| 収録物識別子 | AA11560603 | |||||||
| 書誌情報 |
情報処理学会論文誌コンピュータビジョンとイメージメディア（CVIM） 巻 49, 号 SIG6(CVIM20), p. 68-78, 発行日 2008-03-15 |
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| ISSN | ||||||||
| 収録物識別子タイプ | ISSN | |||||||
| 収録物識別子 | 1882-7810 | |||||||
| 出版者 | ||||||||
| 言語 | ja | |||||||
| 出版者 | 情報処理学会 | |||||||
