PhD Thesis - Automated Recognition of 3D CAD Model Objects in ...

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5.2.1 Progress Calculation Method . . . . . . . . . . . . . . . . . 68 5.2.2 Experimental Results . . . . . . . . . . . . . . . . . . . . . . 69 5.2.3 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 5.3 APPC: Automated Dimensional QA/QC . . . . . . . . . . . . . . . 75 5.4 APPC: Automated Dimensional Health Monitoring . . . . . . . . . 76 5.5 Planning For Scanning . . . . . . . . . . . . . . . . . . . . . . . . . 76 5.5.1 Experiment . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 5.6 Strategic Scanning . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 6 Conclusions and Recommendations 81 6.1 Contribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 6.2 Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 6.3 Suggestions for Future Research . . . . . . . . . . . . . . . . . . . . 83 Appendices 85 A Description of the STL Format 85 B The Spherical Coordinate Frame 88 B.1 The Spherical Coordinate Frame . . . . . . . . . . . . . . . . . . . . 88 B.2 Coordinate Frame Conversions . . . . . . . . . . . . . . . . . . . . . 89 B.2.1 Spherical to Cartesian . . . . . . . . . . . . . . . . . . . . . 89 B.2.2 Cartesian to Spherical . . . . . . . . . . . . . . . . . . . . . 89 C Calculation of the Minimum Spherical Angular Bounding Volumes (MSABVs) of STL Entities 92 C.1 MSABV of a STL Facet . . . . . . . . . . . . . . . . . . . . . . . . 93 C.1.1 Bounding Pan Angles: ϕmin and ϕmax . . . . . . . . . . . . 95 C.1.2 Bounding Tilt Angles: θmin and θmax . . . . . . . . . . . . . 100 C.2 MSABV of a STL Object . . . . . . . . . . . . . . . . . . . . . . . 100 viii
D Construction of the Bounding Volume Hierarchy (BVH) of a project 3D Model 105 D.1 Back-Facing Facet Culling . . . . . . . . . . . . . . . . . . . . . . . 105 D.2 Scan’s Viewing Frustum Culling . . . . . . . . . . . . . . . . . . . . 107 D.2.1 Calculation of a Scan’s Viewing Frustum . . . . . . . . . . . 107 D.2.2 Does a STL Entity Intersect a Scan’s Viewing Frustum? . . 108 D.3 Calculation of the BVH . . . . . . . . . . . . . . . . . . . . . . . . 111 E Containment of a Ray in a Minimum Spherical Angular Bounding Volume (MSABV). 113 F Calculation of the Range of the Intersection Point of a Ray and a STL Facet 117 F.1 Is Projected Point Inside Facet? . . . . . . . . . . . . . . . . . . . . 118 G Object Recognition Results of Experiment 3 122 G.1 Input Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122 G.2 Recognition Process Results . . . . . . . . . . . . . . . . . . . . . . 124 G.2.1 Step 1 - Convert 3D model . . . . . . . . . . . . . . . . . . . 124 G.2.2 Step 2 - 3D model Scan-Referencing . . . . . . . . . . . . . . 125 G.2.3 Step 3 - Calculate As-planned Range Point Cloud . . . . . . 126 G.2.4 Step 4 - Recognize Points . . . . . . . . . . . . . . . . . . . 127 G.2.5 Step 5 - Recognize Objects . . . . . . . . . . . . . . . . . . . 128 G.2.6 Recognition Statistics . . . . . . . . . . . . . . . . . . . . . . 130 H Notation 142 References 146 ix
Page 1 and 2: Automated Recognition of 3D CAD Mod
Page 3 and 4: Abstract There is shift in the Arch
Page 5 and 6: Dedication This thesis is dedicated
Page 7: 3.4 Step 3 - Calculation of the As-
Page 11 and 12: 5.4 Progress recognition results fo
Page 13 and 14: 5.2 Example of a model and recogniz
Page 15 and 16: Chapter 1 Introduction 1.1 Backgrou
Page 17 and 18: Introduction 3 Sub-objectives are f
Page 19 and 20: Chapter 2 Literature Review This ch
Page 21 and 22: Literature Review 7 is also often i
Page 23 and 24: Literature Review 9 Figure 2.2: Tot
Page 25 and 26: Literature Review 11 minutes (at mo
Page 27 and 28: Literature Review 13 tigated here.
Page 29 and 30: Literature Review 15 the recognitio
Page 31 and 32: Literature Review 17 recognition of
Page 33 and 34: Literature Review 19 frame of the e
Page 35 and 36: Chapter 3 New Approach 3.1 Overview
Page 37 and 38: New Approach 23 Data: Model, Scan R
Page 39 and 40: New Approach 25 frame. Therefore, f
Page 41 and 42: New Approach 27 The complexity of t
Page 43 and 44: New Approach 29 are tested for inte
Page 45 and 46: New Approach 31 effectiveness of a
Page 47 and 48: New Approach 33 (a) 3D View. (b) To
Page 49 and 50: New Approach 35 Data: PB, BVH Resul
Page 51 and 52: New Approach 37 α, of each as-plan
Page 53 and 54: New Approach 39 Data: Scan,Model Re
Page 55 and 56: New Approach 41 where: α is the as
Page 57 and 58: New Approach 43 Furthermore, the ca
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Chapter 4 Experimental Analysis of
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Experimental Analysis of the Approa
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Chapter 5 Enabled Applications: Fea
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Enabled Applications: Feasibility A
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Chapter 6 Conclusions and Recommend
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Conclusions and Recommendations 83
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Appendix A Description of the STL F
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Appendix A 87 solid name facet norm
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Appendix B 89 Figure B.1: Spherical
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Appendix B 91 Data: [x, y, z] Resul
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Appendix C 93 (a) 3D View. (b) Top
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Appendix C 95 C.1.1 Bounding Pan An
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Appendix C 97 Figure C.5: Illustrat
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Appendix C 99 Data: ϕmintemp, ϕmi
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Appendix C 101 Figure C.6: Example
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Appendix C 103 Data: {Facet} Result
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Appendix D Construction of the Boun
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Appendix D 107 Figure D.1: Illustra
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Appendix D 109 (a) MSABV not inters
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Appendix D 111 It can be noted that
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Appendix E Containment of a Ray in
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Appendix E 115 Finally, in the case
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Appendix F Calculation of the Range
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Appendix F 119 second plane perpend
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Appendix F 121 included in Algorith
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Appendix G 123 Figure G.1: 3D CAD m
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Appendix G 125 G.2.2 Step 2 - 3D mo
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Appendix G 127 G.2.4 Step 4 - Recog
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Appendix G 129 It can be seen in Fi
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Appendix G 131 Column 7: Whether th
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Appendix G 133 Table G.1 - continue
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Appendix H 143 Table H.1 - continue
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Appendix H 145 Table H.2 - continue
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Appendix H 147 [11] J. Amanatides.
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Appendix H 149 [35] G. S. Coleman a
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Appendix H 151 [57] B. Hofmann-Well
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Appendix H 153 [81] A. S. Mian, M.
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Appendix H 155 [104] L. M. Sheppard
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PhD Thesis - Automated Recognition of 3D CAD Model Objects in ...

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