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Distance Transforms for Large Volumetric Models using External Memory
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- MICHIKAWA Takashi
- RCAST, The University of Tokyo
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- TSUJI Ken'ichiro
- Oracle Corporation Japan
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- SUZUKI Hiromasa
- RCAST, The University of Tokyo
Bibliographic Information
- Other Title
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- 外部メモリを利用した大規模ボリュームデータに対する距離変換手法
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Description
This paper presents a method for computing distance fields from large volumetric models.Conventional methods have limits in terms of the amount of memory space, as all of data must be allocated to the RAM.We resolve this issue by using an out-of-core strategy. Proposed method first decomposes volumetric models into sub-blocked clusters and applies distance transforms to each cluster. Then, other clusters can be saved on the bulk memory. In addition, we apply inter-cluster propagation to remove inconsistency of distance fields. We also propose an ordering algorithm for reducing the number of distance transforms for each cluster by using propagated distance values. Finally, this paper demonstrates to calculate distance fields with over billion cells in practical time.
Journal
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- Proceedings of the Annual Conference of the Institute of Image Electronics Engineers of Japan
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Proceedings of the Annual Conference of the Institute of Image Electronics Engineers of Japan 35vc (0), 215-220, 2007
The Institute of Image Electronics Engineers of Japan
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Details 詳細情報について
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- CRID
- 1390001205610057216
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- NII Article ID
- 130006966807
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- ISSN
- 24364398
- 24364371
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- Data Source
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- JaLC
- CiNii Articles
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- Abstract License Flag
- Disallowed