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3D Modeling: Surface Reconstruction and Surface Simplification

3D Modeling: Surface Reconstruction and Surface Simplification. 曾俊霖 明新科技大學 資訊工程系. 3D Modeling. What is 3D Modeling ? 3D modeling is the process of developing a mathematical, wireframe representation of any three-dimensional object (either inanimate or living) via specialized software.

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3D Modeling: Surface Reconstruction and Surface Simplification

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  1. 3D Modeling:Surface Reconstruction and Surface Simplification 曾俊霖 明新科技大學 資訊工程系 國立新竹教育大學資科所/明新科技大學資工系

  2. 3D Modeling • What is 3D Modeling? • 3D modeling is the process of developing a mathematical, wireframe representation of any three-dimensional object (either inanimate or living) via specialized software. • Why3D Modeling? • Virtual Reality is springing up. • 3D is friendlier than 2D. • In the future • See a movie 國立新竹教育大學資科所/明新科技大學資工系

  3. 3D Modeling • How to model a 3D object? • Sequential Engineering (順向工程) • Creating an inexistent object. • Using 3D modeling softwares. • 3D Studio Max, Maya, … • Reverse Engineering(逆向工程) • Creating an existent object. • Using production procedure of Reverse Engineering 國立新竹教育大學資科所/明新科技大學資工系

  4. CD ROM /Virtual ShowRoom OFF-Line Planner Demonstrator Support Configurator 3D Studio MAX Maya LightWave trueSpace ProE SolidWork SolidEdge AutoCAD ArchiCAD Flash Director Concave/Immersive 虛擬實境顯示融 入操控模擬系統 WEB 3D CAD Server/Collosseum Studio/SDK 虛擬實境開 發應用/軟體 Integrated Digital Content ON-Line Animation Mobile Visualizer Mobile Multimedia ASP HTML XML Linux JAVA VB VC++ ActiveX MS Agent Mov MP3 Avi PPM 3D(影像/幾何) 擷取編輯系統 資料庫 ORACLE 國立新竹教育大學資科所/明新科技大學資工系

  5. Reverse Engineering • Production procedure (Step 1) • Creation of a digital object • A point-cloud model • Using a 3D scanner 國立新竹教育大學資科所/明新科技大學資工系

  6. Reverse Engineering • Production procedure (Step 2) • Creation of a meshed model • Using surface reconstructionmethod 國立新竹教育大學資科所/明新科技大學資工系

  7. Surface Reconstruction • Generating the triangles from a point-cloud model 國立新竹教育大學資科所/明新科技大學資工系

  8. Surface Reconstruction • Problems • Which two points should be formed an edge? • How to decrease the time cost of generating a meshed model? 國立新竹教育大學資科所/明新科技大學資工系

  9. Surface Reconstruction • Key steps • Localized sampling • Fixed-sized sampling approach • Alpha ball (sampling size determined by users) α=0 α=∞ 國立新竹教育大學資科所/明新科技大學資工系

  10. Surface Reconstruction • Key steps • Localized sampling • Fixed-sized sampling approach • LVC (size determined by whole model points) • Proposed by Jong and Juin at CYCU in 2005 • γ = γm + 3s • γm is the average of the distance from the closest point 國立新竹教育大學資科所/明新科技大學資工系

  11. Surface Reconstruction • Key steps • Localized sampling • Fixed-sized sampling approach • LVC (size determined by whole model points) • Problem: some undesired edges are generated. 國立新竹教育大學資科所/明新科技大學資工系

  12. Surface Reconstruction • Key steps • Localized sampling • Adaptive-sized sampling approach • Projected-based approach • Proposed by Gopi in 2002 • Using the nearest point to determine the sampling region • r= μ x m • Dense points are necessary. • Small holes might be generated. 國立新竹教育大學資科所/明新科技大學資工系

  13. Surface Reconstruction • Key steps • Localized sampling • Adaptive-sized sampling approach • Shape-based approach • Proposed by Jong and Juin • Summit to JCST(SCI Journal) - 2nd revised • Using DSO(Discrete Shape Operator) to determine the sampling regions 國立新竹教育大學資科所/明新科技大學資工系

  14. Surface Reconstruction • Key steps • Sampling points pruning • Points lying on different surfaces 國立新竹教育大學資科所/明新科技大學資工系

  15. Surface Reconstruction • Key steps • Sampling points pruning • Points lying on different surfaces 國立新竹教育大學資科所/明新科技大學資工系

  16. Surface Reconstruction • Current Results 國立新竹教育大學資科所/明新科技大學資工系

  17. Surface Reconstruction • Another problem • The reconstruction of high-variation surfaces fails easily. • Solution • Extracting high-variation surfaces before reconstructing • The number of points is too many • Increasing of computation cost • Increasing of storage cost • Solution • Removing some irrelevant points and triangles • Using Surface Simplification Method 國立新竹教育大學資科所/明新科技大學資工系

  18. Surface Simplification • Reduce the points and triangles • Problems • Which points, edges or triangles should be removed? 國立新竹教育大學資科所/明新科技大學資工系

  19. Surface Simplification • Related Methods • Vertex Removal • removing a vertex from 3D model, along with its adjacent edges and triangles, and retriangulating the resulting hole. • Only for manifold surface 國立新竹教育大學資科所/明新科技大學資工系

  20. Surface Simplification • Related Method • Vertex Clustering • It cannot maintain the quality. 國立新竹教育大學資科所/明新科技大學資工系

  21. Surface Simplification • Related Methods • Edge Collapse • Edge collapse can contract an edge to a single vertex. • This approach can be used for manifold and non-manifold models, but can close holes in the model. 國立新竹教育大學資科所/明新科技大學資工系

  22. Surface Simplification • Related Methods • Vertex-Pair Contraction • Using QEM(Quadric Error Metric) to determine the rank of vertex-pair contraction 國立新竹教育大學資科所/明新科技大學資工系

  23. Surface Simplification • Related Methods • Multiphase Approach • Combining the uniform-clustering method and vertex-pair contraction • For large-size models • User-Guided Simplification • This method aims to overcome the problem of vertex-pair contraction to retain the object features. • Retained features determined by users 國立新竹教育大學資科所/明新科技大學資工系

  24. Surface Simplification • Our approach • Using Shape Operator to retain the object features automatically 國立新竹教育大學資科所/明新科技大學資工系

  25. Surface Simplification • Shape Operator • Merge curvature and Torsion 國立新竹教育大學資科所/明新科技大學資工系

  26. Surface Simplification • Vertex-Pair Contraction vs our approach 國立新竹教育大學資科所/明新科技大學資工系

  27. Feature Extraction • Extracting features before surface reconstruction • It can avoid the failure of reconstruction of high-variation surfaces • Extracting features before surface simplification • It can effectively retain the features of a simplified model. 國立新竹教育大學資科所/明新科技大學資工系

  28. Feature Extraction • Correlation ellipsoid 國立新竹教育大學資科所/明新科技大學資工系

  29. Feature Extraction • Multi-scale feature extraction 國立新竹教育大學資科所/明新科技大學資工系

  30. Feature Extraction • Time cost is very high. • Low-cost feature extraction method is necessary • Using DSO to extract high-variation surfaces 國立新竹教育大學資科所/明新科技大學資工系

  31. Feature Extraction • For point-based models 國立新竹教育大學資科所/明新科技大學資工系

  32. Feature Extraction • For meshed models • 1-ring neighbors 國立新竹教育大學資科所/明新科技大學資工系

  33. Feature Extraction • Point-based models 國立新竹教育大學資科所/明新科技大學資工系

  34. Feature Extraction • Meshed models 國立新竹教育大學資科所/明新科技大學資工系

  35. Computer Graphics in the Future • A movie generated by NTT in Japan • NTT Docomo -Vision2010 • 2003~2010 <movie> • NTT Docomo -Vision2010 • 198x~201x <movie> 國立新竹教育大學資科所/明新科技大學資工系

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