3D Modeling: Surface Reconstruction and Surface Simplification 曾俊霖 明新科技大學 資訊工程系 2007/11/15 國立新竹教育大學資科所 / 明新科技大學資工系

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. Why 3D Modeling? ◦ Virtual Reality is springing up. ◦ 3D is friendlier than 2D. ◦ In the future  See a movie 2007/11/15 國立新竹教育大學資科所 / 明新科技大學資工系 2

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 2007/11/15 國立新竹教育大學資科所 / 明新科技大學資工系 3

2007/11/15 國立新竹教育大學資科所 / 明新科技大學資工系 4 3D( 影像 / 幾何 ) 擷取編輯系統 虛擬實境開 發應用 / 軟體 虛擬實境顯示融 入操控模擬系統 Multimedia Animation 3D CAD Concave/Immersive Studio/SDK OFF-Line CD ROM /Virtual ShowRoom Mobile ON-Line Server/Collosseum Mobile Visualizer Configurator Support Demonstrator Planner Integrated Digital Content 3D Studio MAX Maya LightWave trueSpace ProE SolidWork SolidEdge AutoCAD ArchiCAD Flash Director 資料庫 WEB ORACLE ASPHTMLXMLLinuxJAVAVBVC++ ActiveX MS Agent MovMP3AviPPM

Reverse Engineering Production procedure (Step 1) ◦ Creation of a digital object  A point-cloud model  Using a 3D scanner 2007/11/15 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 2) ◦ Creation of a meshed model  Using surface reconstruction method 2007/11/15 國立新竹教育大學資科所 / 明新科技大學資工系 6

Surface Reconstruction Generating the triangles from a point- cloud model 2007/11/15 國立新竹教育大學資科所 / 明新科技大學資工系 7

Surface Reconstruction Problems ◦ Which two points should be formed an edge? ◦ How to decrease the time cost of generating a meshed model? 2007/11/15 國立新竹教育大學資科所 / 明新科技大學資工系 8

Surface Reconstruction Key steps ◦ Localized sampling  Fixed-sized sampling approach  Alpha ball (sampling size determined by users) 2007/11/15 國立新竹教育大學資科所 / 明新科技大學資工系 9 α=∞α=∞ α =0

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 = γ m + 3s  γ m is the average of the distance from the closest point 2007/11/15 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)  Problem: some undesired edges are generated. 2007/11/15 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  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. 2007/11/15 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  Shape-based approach  Proposed by Jong and Juin  Summit to JCST(SCI Journal) - 2 nd revised  Using DSO(Discrete Shape Operator) to determine the sampling regions 2007/11/15 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 ◦ Sampling points pruning  Points lying on different surfaces 2007/11/15 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 2007/11/15 國立新竹教育大學資科所 / 明新科技大學資工系 15

Surface Reconstruction Current Results 2007/11/15 國立新竹教育大學資科所 / 明新科技大學資工系 16

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 2007/11/15 國立新竹教育大學資科所 / 明新科技大學資工系 17

Surface Simplification Reduce the points and triangles Problems ◦ Which points, edges or triangles should be removed? 2007/11/15 國立新竹教育大學資科所 / 明新科技大學資工系 18

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 2007/11/15 國立新竹教育大學資科所 / 明新科技大學資工系 19

Surface Simplification Related Method ◦ Vertex Clustering  It cannot maintain the quality. 2007/11/15 國立新竹教育大學資科所 / 明新科技大學資工系 20

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. 2007/11/15 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 ◦ Vertex-Pair Contraction  Using QEM(Quadric Error Metric) to determine the rank of vertex-pair contraction 2007/11/15 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 ◦ 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 2007/11/15 國立新竹教育大學資科所 / 明新科技大學資工系 23

Surface Simplification Our approach ◦ Using Shape Operator to retain the object features automatically 2007/11/15 國立新竹教育大學資科所 / 明新科技大學資工系 24

Surface Simplification Shape Operator ◦ Merge curvature and Torsion 2007/11/15 國立新竹教育大學資科所 / 明新科技大學資工系 25

Surface Simplification Vertex-Pair Contraction vs our approach 2007/11/15 國立新竹教育大學資科所 / 明新科技大學資工系 26

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. 2007/11/15 國立新竹教育大學資科所 / 明新科技大學資工系 27

Feature Extraction Correlation ellipsoid 2007/11/15 國立新竹教育大學資科所 / 明新科技大學資工系 28

Feature Extraction Multi-scale feature extraction 2007/11/15 國立新竹教育大學資科所 / 明新科技大學資工系 29

Feature Extraction Time cost is very high. Low-cost feature extraction method is necessary ◦ Using DSO to extract high-variation surfaces 2007/11/15 國立新竹教育大學資科所 / 明新科技大學資工系 30

Feature Extraction For point-based models 2007/11/15 國立新竹教育大學資科所 / 明新科技大學資工系 31

Feature Extraction For meshed models ◦ 1-ring neighbors 2007/11/15 國立新竹教育大學資科所 / 明新科技大學資工系 32

Feature Extraction Point-based models 2007/11/15 國立新竹教育大學資科所 / 明新科技大學資工系 33

Feature Extraction Meshed models 2007/11/15 國立新竹教育大學資科所 / 明新科技大學資工系 34

Computer Graphics in the Future A movie generated by NTT in Japan ◦ NTT Docomo -Vision2010  2003~2010 movie ◦ NTT Docomo -Vision2010  198x~201x movie 2007/11/15 國立新竹教育大學資科所 / 明新科技大學資工系 35