Seminario Ruggero Pintus, 4-10-2012

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I moderni sistemi di acquisizione 3D sono capaci di digitalizzare rapidamente la geometria e il colore di oggetti con alta accuratezza e risoluzione, producendo modelli 3D digitali con miliardi di punti. Questi modelli sono estremamente adatti nel campo dei Beni Culturali, dove è richiesto un alto livello di campionamento. Questo seminario si concentrerà su due importanti tecniche: un metodo semplice, veloce e robusto per l'allineamento semi-automatico di geometria e colore capace di gestire grandi insiemi di immagini, e un framework di blending di immagini su geometria capace di produrre modelli colorati di grandi dimensioni. L'efficacia di queste tecniche verrà dimostrata su una serie di dati reali nel campo dei Beni Culturali.

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Seminario Ruggero Pintus, 4-10-2012

  1. 1. www.crs4.it/vic/ Tecnologie di Visual Computing per i Beni CulturaliR. PintusCRS4 Visual Computing
  2. 2. R. Pintus – CRS4/ViC, October 2012Tecnologie per i beni culturali• Focus: digitalizzazione accurata (forma e colore) di siti e manufatti + … – Partire dai dati: Acquisizione -> Trattamento ! – Modelli misurabili• Molti usi oltre la visualizzazione – Riproduzione materica – Studio di opere d’arte – Documentazione in-situ di scavi archeologici – Supporto al restauro e sua documentazione – Valorizzazione
  3. 3. R. Pintus – CRS4/ViC, October 2012Tecnologie per i beni culturali• Le quantità di dati prodotte dai moderni sensori sono però difficili da trattare, archiviare, distribuire, visualizzare – Scalabilità!• Tecniche attuali sub-ottimali – Costi, tempi, qualità• Bisogno di ricerca in tecnologie abilitanti scalabili – Acquisizione – Processamento geometrico – Visualizzazione – …
  4. 4. R. Pintus – CRS4/ViC, October 2012Tecnologie per i beni culturali• Come acquisire e processare efficacemente forma e colore di siti e manufatti? – Tecniche di fusione multi-sensore, stream-processing, multiresolution, external memory algorithms, parallel programming, GPGPUs• Come archiviare e distribuire efficacemente i modelli? – Multiresolution, adaptive streaming, compression• Come visualizzarli efficacemente? – Multiresolution, adaptive rendering, out-of-core methods, GPU programming, parallelization, rasterization, ray-casting• Come esplorarli? – Novel 3D displays, specific interaction techniques – Portable devices
  5. 5. R. Pintus – CRS4/ViC, October 2012Alcuni esempi• Allineamento geometria/colore• Colorazione di modelli 3D• Fusione di dati e ricostruzione geometrica• Visualizzazione scalabile ed interattiva• Distribuzione di dati in rete• Esplorazione su display innovativi(… e molto altro)
  6. 6. R. Pintus – CRS4/ViC, October 2012Our Goal 6
  7. 7. R. Pintus – CRS4/ViC, October 2012Modelling vs Acquisition Modelling Subjective Reality Acquisition Objective reality 7
  8. 8. R. Pintus – CRS4/ViC, October 20123D Reconstruction• Acquire geometry and color• A lot of techniques – Structured light, laser scanning (triangulation or time-of-flight), photometric stereo, shape-from-X, …• Which technique? – Object type (big/small, material….) – Cost – Accuracy/Resolution – Time – Complexity 8
  9. 9. R. Pintus – CRS4/ViC, October 2012Outline• 3D Reconstruction Techniques• 3D Reconstruction Pipeline – Photo mapping/blending – Printing• Case study 9
  10. 10. R. Pintus – CRS4/ViC, October 2012Taxonomy (non-destructive) (non- • Contact – Direct Measurements • rulers, calipers, pantographs, coordinate measuring machines (CMM), AFM • Non-Contact – Passive – Active • Shape-from-X • Transmissive – Stereo – Computed Tomography (CT) – Multiview – Transmissive Ultrasound – Silhouettes • Reflective – Focus/Defocus – Non-Optical Methods » reflective ultrasound, radar, sonar, MRI – Time-of-Flight – Triangulation » laser striping » structured lighting – Photometric Stereo 10
  11. 11. R. Pintus – CRS4/ViC, October 2012Taxonomy (non-destructive) (non- • Contact – Direct Measurements • rulers, calipers, pantographs, coordinate measuring machines (CMM), AFM • Non-Contact – Passive – Active • Shape-from-X • Transmissive – Stereo – Computed Tomography (CT) – Multiview – Transmissive Ultrasound – Silhouettes • Reflective – Focus/Defocus – Non-Optical Methods » reflective ultrasound, radar, sonar, MRI – Time-of-Flight – Triangulation » laser striping » structured lighting – Photometric Stereo 11
  12. 12. R. Pintus – CRS4/ViC, October 2012Taxonomy (non-destructive) (non- • Contact – Direct Measurements • rulers, calipers, pantographs, coordinate measuring machines (CMM), AFM • Non-Contact – Passive – Active • Shape-from-X • Transmissive – Stereo – Computed Tomography (CT) – Multiview – Transmissive Ultrasound – Silhouettes • Reflective – Focus/Defocus – Non-Optical Methods » reflective ultrasound, radar, sonar, MRI – Time-of-Flight – Triangulation » laser striping » structured lighting – Photometric Stereo 12
  13. 13. R. Pintus – CRS4/ViC, October 2012Taxonomy – Stereo 13
  14. 14. R. Pintus – CRS4/ViC, October 2012Taxonomy – Stereo 14
  15. 15. R. Pintus – CRS4/ViC, October 2012Taxonomy (non-destructive) (non- • Contact – Direct Measurements • rulers, calipers, pantographs, coordinate measuring machines (CMM), AFM • Non-Contact – Passive – Active • Shape-from-X • Transmissive – Stereo – Computed Tomography (CT) – Multiview – Transmissive Ultrasound – Silhouettes • Reflective – Focus/Defocus – Non-Optical Methods » reflective ultrasound, radar, sonar, MRI – Time-of-Flight – Triangulation » laser striping » structured lighting – Photometric Stereo 15
  16. 16. R. Pintus – CRS4/ViC, October 2012Taxonomy – Multiview 16
  17. 17. R. Pintus – CRS4/ViC, October 2012Taxonomy – Multiview 17
  18. 18. R. Pintus – CRS4/ViC, October 2012Taxonomy (non-destructive) (non- • Contact – Direct Measurements • rulers, calipers, pantographs, coordinate measuring machines (CMM), AFM • Non-Contact – Passive – Active • Shape-from-X • Transmissive – Stereo – Computed Tomography (CT) – Multiview – Transmissive Ultrasound – Silhouettes • Reflective – Focus/Defocus – Non-Optical Methods » reflective ultrasound, radar, sonar, MRI – Time-of-Flight – Triangulation » laser striping » structured lighting – Photometric Stereo 18
  19. 19. R. Pintus – CRS4/ViC, October 2012Taxonomy – Silhouettes 19
  20. 20. R. Pintus – CRS4/ViC, October 2012Taxonomy (non-destructive) (non- • Contact – Direct Measurements • rulers, calipers, pantographs, coordinate measuring machines (CMM), AFM • Non-Contact – Passive – Active • Shape-from-X • Transmissive – Stereo – Computed Tomography (CT) – Multiview – Transmissive Ultrasound – Silhouettes • Reflective – Focus/Defocus – Non-Optical Methods » reflective ultrasound, radar, sonar, MRI – Time-of-Flight – Triangulation » laser striping » structured lighting – Photometric Stereo 20
  21. 21. R. Pintus – CRS4/ViC, October 2012Taxonomy – Depth fromfocus/defocus 21
  22. 22. R. Pintus – CRS4/ViC, October 2012Taxonomy (non-destructive) (non- • Contact – Direct Measurements • rulers, calipers, pantographs, coordinate measuring machines (CMM), AFM • Non-Contact – Passive – Active • Shape-from-X • Transmissive – Stereo – Computed Tomography (CT) – Multiview – Transmissive Ultrasound – Silhouettes • Reflective – Focus/Defocus – Non-Optical Methods » reflective ultrasound, radar, sonar, MRI – Time-of-Flight – Triangulation » laser striping » structured lighting – Photometric Stereo 22
  23. 23. R. Pintus – CRS4/ViC, October 2012 Taxonomy – TransmissiveComputed Tomography Density Function Trasmissive Ultrasound 23
  24. 24. R. Pintus – CRS4/ViC, October 2012Taxonomy (non-destructive) (non- • Contact – Direct Measurements • rulers, calipers, pantographs, coordinate measuring machines (CMM), AFM • Non-Contact – Passive – Active • Shape-from-X • Transmissive – Stereo – Computed Tomography (CT) – Multiview – Transmissive Ultrasound – Silhouettes • Reflective – Focus/Defocus – Non-Optical Methods » reflective ultrasound, radar, sonar, MRI – Time-of-Flight – Triangulation » laser striping » structured lighting – Photometric Stereo 24
  25. 25. R. Pintus – CRS4/ViC, October 2012Taxonomy – Non-Optical Non- Ultrasound Radar MRI 25
  26. 26. R. Pintus – CRS4/ViC, October 2012Taxonomy (non-destructive) (non- • Contact – Direct Measurements • rulers, calipers, pantographs, coordinate measuring machines (CMM), AFM • Non-Contact – Passive – Active • Shape-from-X • Transmissive – Stereo – Computed Tomography (CT) – Multiview – Transmissive Ultrasound – Silhouettes • Reflective – Focus/Defocus – Non-Optical Methods » reflective ultrasound, radar, sonar, MRI – Time-of-Flight – Triangulation » laser striping » structured lighting – Photometric Stereo 26
  27. 27. R. Pintus – CRS4/ViC, October 2012Taxonomy – Time-of-Flight Time-of- 2d 5.0mt= = ≈ 17ns c 3 × 108 m s 27
  28. 28. R. Pintus – CRS4/ViC, October 2012Taxonomy (non-destructive) (non- • Contact – Direct Measurements • rulers, calipers, pantographs, coordinate measuring machines (CMM), AFM • Non-Contact – Passive – Active • Shape-from-X • Transmissive – Stereo – Computed Tomography (CT) – Multiview – Transmissive Ultrasound – Silhouettes • Reflective – Focus/Defocus – Non-Optical Methods » reflective ultrasound, radar, sonar, MRI – Time-of-Flight – Triangulation » laser striping » structured lighting – Photometric Stereo 28
  29. 29. R. Pintus – CRS4/ViC, October 2012Taxonomy – Laser Striping 29
  30. 30. R. Pintus – CRS4/ViC, October 2012Taxonomy (non-destructive) (non- • Contact – Direct Measurements • rulers, calipers, pantographs, coordinate measuring machines (CMM), AFM • Non-Contact – Passive – Active • Shape-from-X • Transmissive – Stereo – Computed Tomography (CT) – Multiview – Transmissive Ultrasound – Silhouettes • Reflective – Focus/Defocus – Non-Optical Methods » reflective ultrasound, radar, sonar, MRI – Time-of-Flight – Triangulation » laser striping » structured lighting – Photometric Stereo 30
  31. 31. R. Pintus – CRS4/ViC, October 2012Taxonomy – Structured Lighting 31
  32. 32. R. Pintus – CRS4/ViC, October 2012Taxonomy (non-destructive) (non- • Contact – Direct Measurements • rulers, calipers, pantographs, coordinate measuring machines (CMM), AFM • Non-Contact – Passive – Active • Shape-from-X • Transmissive – Stereo – Computed Tomography (CT) – Multiview – Transmissive Ultrasound – Silhouettes • Reflective – Focus/Defocus – Non-Optical Methods » reflective ultrasound, radar, sonar, MRI – Time-of-Flight – Triangulation » laser striping » structured lighting – Photometric Stereo 32
  33. 33. R. Pintus – CRS4/ViC, October 2012Taxonomy – Photometric Stereo 33
  34. 34. R. Pintus – CRS4/ViC, October 2012Photometric Stereo – SEM 34
  35. 35. R. Pintus – CRS4/ViC, October 2012Taxonomy – Photometric Stereo 35
  36. 36. R. Pintus – CRS4/ViC, October 2012Taxonomy SEM • Contact – Direct Measurements • rulers, calipers, pantographs, coordinate measuring machines (CMM), AFM • Non-Contact – Passive – Active • Shape-from-X • Transmissive – Stereo – Computed Tomography (CT) – Multiview – Transmissive Ultrasound – Silhouettes • Reflective – Focus/Defocus – Non-Optical Methods » reflective ultrasound, radar, sonar, MRI – Time-of-Flight – Triangulation » laser striping » structured lighting – Photometric Stereo 36
  37. 37. R. Pintus – CRS4/ViC, October 2012Cultural Heritage• Techniques – Triangulation (laser scanner) – Time of Flight – Texture Mapping – Multi-view reconstruction – Photometric Stereo• Deal with multiple acquisitions• Manage a huge amount of data for visualization purposes 37
  38. 38. R. Pintus – CRS4/ViC, October 20123D Reconstruction PipelineReal Object Acquisition Devices Photos3D Digital Model Geometry === Processing === -Cleaning - Merging - Photo Alignment - Color Projection -… 38
  39. 39. R. Pintus – CRS4/ViC, October 20123D Reconstruction Pipeline• Real Model Inspection (onsite)• Scans design (offsite/onsite)• Acquisition (onsite)• Alignment (offsite)• Editing (offsite)• Merge (offsite)• Texture (offsite)• Final Model (offsite)• 3D Printing (offsite) 39
  40. 40. R. Pintus – CRS4/ViC, October 20123D Reconstruction Pipeline• Real Model Inspection (onsite)• Scans design (offsite/onsite)• Acquisition (onsite)• Alignment (offsite)• Editing (offsite)• Merge (offsite)• Texture (offsite)• Final Model (offsite)• 3D Printing (offsite) 40
  41. 41. R. Pintus – CRS4/ViC, October 2012Goal• Fast and low-cost technique for creating accurate colored models• Acquisition – 3D – laser scanners – Color – digital cameras• Mapping photo-to-geometry – Fast and Robust Semi-Automatic Registration of Photographs to 3D Geometry• Photo blending – A Streaming Framework for Seamless Detailed Photo Blending on Massive Point Clouds
  42. 42. www.crs4.it/vic/ Photo MappingRuggero Pintus, Enrico Gobbetti, and Roberto Combet. “Fast and Robust Semi-AutomaticRegistration of Photographs to 3D Geometry”. In The 12th International Symposium on VirtualReality, Archaeology and Cultural Heritage, October 2011.
  43. 43. R. Pintus – CRS4/ViC, October 2012 Problem Statement3D Geometry Unordered Set Of n Uncalibrated Photos n Camera Poses (2D/3D Registration)
  44. 44. R. Pintus – CRS4/ViC, October 2012Related work• Manual selection of 2D-3D matches – Massive user intervention – Tiring and time-consuming• Automatic feature matching – Not robust enough for a generic dataset• Semi-automatic statistical correlation – Point cloud attributes not always provided• Geometric multi-view reconstruction – 2D-3D problem 3D-3D registration task – dense and ordered frame sequence• Our contribution – Minimize user intervention / Large datasets / Semi- automatic / Multi-view based approach / No Attributes
  45. 45. R. Pintus – CRS4/ViC, October 2012 Input DataUser Dense 3D n Photos • Dense Geometry – Point cloud, triangle mesh, etc. SfM Reconstruction – No attributes – No particular features Coarse Registration • n photos – Naïve constraints: Refinement • Blur, Noise, Under- or over-exposured – Sufficient overlap Output Data
  46. 46. R. Pintus – CRS4/ViC, October 2012 Multi- Multi-viewUser Dense 3D n Photos • Bundler [Snavely et al. 2006] – SfM system for unordered SfM Reconstruction image collections – http://phototour.cs.washingto n.edu/bundler/ Coarse Registration • Output – A sparse point cloud – n camera poses Refinement – SIFT keypoints (projections of sparse 3D points) Output Data
  47. 47. R. Pintus – CRS4/ViC, October 2012 Coarse registrationUser Dense 3D n Photos • Register two point clouds with different: – scales – reference frames SfM Reconstruction – resolutions • Automatic methods are not robust and efficient enough Coarse Registration • User aligns few images (one or more) to the dense geometry Refinement • Affine transformation is applied to all cameras and sparse points Output Data
  48. 48. R. Pintus – CRS4/ViC, October 2012RefinementUser Dense 3D n Photos Pj C1 Q (C2 , p j ) s1, j pj SfM Reconstruction s2 , j NN F ( p j ) Coarse Registration Q (C2 , NN F ( p j )) Refinement C2 E (C , P ) = ∑∑ vij Q (Ci , NN F ( p j )) − si , j N P NC 2 Output Data j =1 i =1
  49. 49. R. Pintus – CRS4/ViC, October 2012 RefinementUser Dense 3D n Photos • Sparse Bundle Adjustment (SBA) – Constants – SIFT keypoints, SfM Reconstruction dense 3D points – Variables – Camera poses, sparse 3D points Coarse Registration – SBA • A Generic SBA C/C++ Package Based on the Levenberg- Marquardt Algorithm Refinement • http://www.ics.forth.gr/~loura kis/sba/ Output Data
  50. 50. R. Pintus – CRS4/ViC, October 2012 Output dataUser Dense 3D n Photos • n camera poses SfM Reconstruction • Input of photo blending – n photos Coarse Registration – n camera poses – Dense 3D geometry Refinement Output Data
  51. 51. R. Pintus – CRS4/ViC, October 2012Results – Photo mapping
  52. 52. www.crs4.it/vic/ Photo BlendingRuggero Pintus, Enrico Gobbetti, and Marco Callieri. A Streaming Framework for Seamless DetailedPhoto Blending on Massive Point Clouds. In Proc. Eurographics Area Papers. Pages 25- 32, 2011.
  53. 53. R. Pintus – CRS4/ViC, October 2012 Problem StatementPoint Cloud Calibrated Photos
  54. 54. R. Pintus – CRS4/ViC, October 2012 Problem StatementPoint Cloud Calibrated Photos P
  55. 55. R. Pintus – CRS4/ViC, October 2012 Problem Statement Calibrated ColoredPoint Cloud Photos Point Cloud P
  56. 56. R. Pintus – CRS4/ViC, October 2012 Problem Statement Calibrated Colored Point Cloud Photos Point Cloud P• Problem Unlimited size of 3D model (Gpoints) and unlimited number of images
  57. 57. R. Pintus – CRS4/ViC, October 2012Related work• State-of-the-art techniques – Image quality estimation – Stitching or blending• Data representation – Triangle meshes – exploit connectivity – Meshless approaches • Both triangle meshes and point clouds• Memory settings – All in-core – no massive geometry/images – 3D in-core and images out-of-core – no massive geometry – All out-of-core – Low performances• Our contribution – Blending function / Streaming framework / Massive point cloud / Adaptive geometry refinement
  58. 58. R. Pintus – CRS4/ViC, October 2012Pipeline Masked Per-pixel Photo Stencil Per-pixel Weight Weight
  59. 59. R. Pintus – CRS4/ViC, October 2012Simple blending
  60. 60. R. Pintus – CRS4/ViC, October 2012Edge extraction and DistanceTransform
  61. 61. R. Pintus – CRS4/ViC, October 2012Smooth weight
  62. 62. R. Pintus – CRS4/ViC, October 2012Smooth weight
  63. 63. R. Pintus – CRS4/ViC, October 2012Single band blending
  64. 64. R. Pintus – CRS4/ViC, October 2012Multi band blending
  65. 65. R. Pintus – CRS4/ViC, October 2012Adaptive point refinement
  66. 66. R. Pintus – CRS4/ViC, October 2012Adaptive point refinement
  67. 67. R. Pintus – CRS4/ViC, October 2012Adaptive point refinement
  68. 68. R. Pintus – CRS4/ViC, October 2012Adaptive point refinement
  69. 69. R. Pintus – CRS4/ViC, October 2012Results David • Callieri et. al 2008 – David 28M 470Mpoints – Disk space occupancy – 6.2GB – Computation time – 15.5 hours
  70. 70. R. Pintus – CRS4/ViC, October 2012Results – Church’s Apse 14 Mpoint Geometry 40 photos
  71. 71. R. Pintus – CRS4/ViC, October 2012Results – Church’s Apse
  72. 72. R. Pintus – CRS4/ViC, October 2012Results – Grave 21 photos8 Mpoint Geometry
  73. 73. R. Pintus – CRS4/ViC, October 2012Results – Grave
  74. 74. R. Pintus – CRS4/ViC, October 2012Results
  75. 75. R. Pintus – CRS4/ViC, October 2012Results
  76. 76. R. Pintus – CRS4/ViC, October 2012Results David 470MpointsImage size – 19456x53248 1Gpixel
  77. 77. R. Pintus – CRS4/ViC, October 2012Results
  78. 78. R. Pintus – CRS4/ViC, October 2012Conclusion• Image-to-geometry registration approach• Minimum user intervention• No constraints on geometry, attributes and features• Specific robust cost function and SBA• Out-of-core photo blending approach (Point clouds of unlimited size)• Incremental color accumulation (Unlimited number of images)• Smooth weight function (Seamless color blending)• Streaming framework (Performance improvement)• Adaptive point refinement• Future work – Automatic sparse-to-dense geometry registration – Interactive blending - adding and removing images in an interactive tool – Fast visual check of previous alignment step
  79. 79. R. Pintus – CRS4/ViC, October 2012Conclusion• Low cost – Personal computer – Digital camera – Decreased manual intervention• Open Source / Free Software – Bundler – SfM reconstruction – http://phototour.cs.washington.edu/bundler/ – Sparse Bundle Adjustment – SBA – Minimization – http://www.ics.forth.gr/~lourakis/sba/ – Opengl / GLSL shaders – Rendering – http://www.opengl.org/ – Qt – Interface – http://qt.nokia.com/ – Opencv – Manual registration – http://opencv.willowgarage.com/wiki/ – Spaceland Library – Geometric computation – http://spacelib.sourceforge.net/ – IIPImage – Web-based Viewer – http://iipimage.sourceforge.net/
  80. 80. R. Pintus – CRS4/ViC, October 20123D Printing 80
  81. 81. R. Pintus – CRS4/ViC, October 2012Printing Process • Original model • Slice representation • Layer by layer deposition • Cleaning • Printed model 81
  82. 82. R. Pintus – CRS4/ViC, October 2012Printing Process • Original model • Slice representation • Layer by layer deposition • Cleaning • Printed model 82
  83. 83. R. Pintus – CRS4/ViC, October 2012Printing Process • Original model • Slice representation • Layer by layer deposition • Cleaning • Printed model 83
  84. 84. R. Pintus – CRS4/ViC, October 2012Printing Process • Original model • Slice representation • Layer by layer deposition • Cleaning • Printed model 84
  85. 85. R. Pintus – CRS4/ViC, October 2012Printing Process • Original model • Slice representation • Layer by layer deposition • Cleaning • Printed model 85
  86. 86. R. Pintus – CRS4/ViC, October 2012Geometry processing 86
  87. 87. R. Pintus – CRS4/ViC, October 2012Geometry processing 87
  88. 88. R. Pintus – CRS4/ViC, October 2012Geometry processing 88
  89. 89. R. Pintus – CRS4/ViC, October 2012Sub-Sub-surface scattering 89
  90. 90. R. Pintus – CRS4/ViC, October 2012Color enhancement 90
  91. 91. R. Pintus – CRS4/ViC, October 2012Color enhancement 91
  92. 92. R. Pintus – CRS4/ViC, October 2012Color enhancement 92
  93. 93. R. Pintus – CRS4/ViC, October 2012Conclusioni• Lavorare su dati misurati è un pre- requisito di molti lavori (tutti?) nel contesto dei beni culturali – Applicazioni specialistiche o per grande pubblico• Le moderne tecnologie di acquisizione consentono di acquisire una grande quantità di informazioni (forma e colore) – Laser scanning, camere digitali, ecc.• Uso potenziale vasto! – Valorizzazione, restauro, studio, ecc.
  94. 94. R. Pintus – CRS4/ViC, October 2012Conclusioni• Queste quantità di dati sono però difficili da trattare, archiviare, distribuire, visualizzare – Scalabilità!• Tecniche attuali sub-ottimali – Costi, tempi, qualità
  95. 95. R. Pintus – CRS4/ViC, October 2012Conclusioni• Il CRS4 è impegnato in attività di ricerca per migliorare le tecnologie… – Stato dell’arte internazionale – Collaborazioni e ricadute locali • PMI, Contro Restauro SS, Soprintendenze, CNR, UniCA• … e per applicarle a casi concreti – Collaborazioni multidisciplinari!
  96. 96. R. Pintus – CRS4/ViC, October 2012Conclusioni 96
  97. 97. R. Pintus – CRS4/ViC, October 2012Questions & Contacts • CRS4 – VIC www.crs4.it/vic/ • Ruggero Pintus ruggero@crs4.it

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