| Project/Area Number |
16300021
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Media informatics/Database
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| Research Institution | Iwate University |
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Principal Investigator |
CHIBA Norishige Iwate University, Faculty of Engineering, Professor, 工学部, 教授 (40171946)
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| Co-Investigator(Kenkyū-buntansha) |
FUJIMOTO Tadahiro Iwate University, Faculty of Engineering, Associate Professor, 工学部, 助教授 (00312512)
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| Project Period (FY) |
2004 – 2006
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| Project Status |
Completed (Fiscal Year 2006)
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| Budget Amount *help |
¥14,500,000 (Direct Cost: ¥14,500,000)
Fiscal Year 2006: ¥4,700,000 (Direct Cost: ¥4,700,000)
Fiscal Year 2005: ¥5,000,000 (Direct Cost: ¥5,000,000)
Fiscal Year 2004: ¥4,800,000 (Direct Cost: ¥4,800,000)
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| Keywords | point-based modeling / point-based rendering / depth image / particle / GPU / LOD / range sensor / volume rendering / ポイントベースモデリング / パーティクルベースシミュレーション |
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| Research Abstract |
In this study, we developed several kinds of CG techniques related to a set of points as a fundamental geometric model: modeling and rendering techniques, mutual transformation techniques among a set of points and another model, especially a polygon model. The following models are regarded as a set of points : 2D scalar grid fields such as depth images obtained by a range scanner and DEM(Digital Elevation Model), 3D scalar grid field such as medical images, voxel spaces, 3D textures and point clouds mainly obtained by a particle simulation. The approaches of rendering techniques are classified into those: to apply a conventional polygon rendering to a polygon model transformed from a set of point, to apply point-based rendering directly to a set of points, and to apply point-based rendering to a set of points transformed from another type of model. Especially, the latter approach is expected as a most possible method having the abilities of LOD(Level Of Detail) and anti-aliasing indispensable to render broad natural landscape sceneries including huge amount of complex objects like trees.
In this study, we developed the following techniques for handling a set of points
1.Modeling techniques for depth images
(1.1)Position matching algorithms for integrating multiple depth images
(1.2)Algorithms for making the distribution of points uniform
(1.3)An algorithm for adapting geometric primitive to depth image using Genetic Algorithm
2.Rendering algorithm for voxel spaces
(2.1)An edge preserving algorithm for smoothing normal
3.Surface generation algorithms from a set of points
(3.1)A level-set algorithm using velocity fields
(3.2)A recursive algorithm for finding a polygon hull
4.Point-based rendering
(4.1)Point-based rendering for simulating first order scattering
(4.2)An algorithm for transforming a polygon model to a 3D texture
(4.3)An algorithm for transforming a polygon model to a point cloud
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