ONTOLOGY-DRIVEN 3D RECONSTRUCTION OF ARCHITECTURAL OBJECTS

Christophe Cruz, Franck Marzani, Frank Boochs

2007

Abstract

This paper presents an ontology-driven 3D architectural reconstruction approach based on the survey with a 3D scanner. This solution is powerful in the field of civil engineering projects to save time during the cost process estimation. This time is saved using efficient scanning instruments and a fast reconstruction of a digital mock-up that can be used in specific software. The reconstruction approach considers the three following issues. How to define an ontology to drive the reconstruction process? How to find semantic objects in a cloud of points? How to control an algorithm in order to find all objects in the cloud of points? This paper underlines the solutions found for these questions.

References

  1. Amann B., 2003. Du Partage centralisé de ressources Web centralisées à l'échange de documents intensionnels, Documents de Synthèse, 2003.
  2. Bachimont B., 2000. Engagement sémantique et engagement ontologique : conception et réalisation d'ontologie en ingénierie des connaissances, In Charlet J., Zackland M., Kessel G. & Bourigault D., eds., Ingénierie des connaissances : évolution récentes et nouveaux défis, Eyrolles, pages 305-323.
  3. Backer H. H. & Binford T. O., 1981. Depth from edge and intensity based stereo. In Proceedinds of the seventh IJCAI, Vancouver, BC, pages 631-636.
  4. Balletti C. & Mander S., 2004. Contemporary Master's Architecture: New Architectural Heritage, Approaches For Surveying and Representation, Geo-Imagery Bridging Continents, XXth ISPRS Congress, 12-23 July, Istanbul, Turkey.
  5. Boehler W. & al., 2004. The potential of non-contact close range laser scanners for cultural heritage recording, Actes du XVIII Symposium International CIPA, Postdam, Allemagne.
  6. Bougnoux S. & Robert L, 1997, TotalCalib: a fast and reliable system for off-line calibration of images sequences., In Proceedings of International Conference on Computer Vision and Pattern Recognition, The Demo Session.
  7. Bryan P.G., Corner I. & Stevens D., 1999. Digital Rectification Techniques for Architectural and Archaeological, Photogrammetric Record, 16(93): 399-415, April.
  8. Cantzler H., Fisher R. B. & Devy M., 2002. Quality enhancement of reconstructed 3D models using coplanarity and constraints, Proc. Annual German Symposium for Pattern Recognition (DAGM02, Zurich), pp 34-41.
  9. Dechilly T. & Bachimont B., 2000. Une ontologie pour éditer des schémas de description audiovisuels, extension pour l'inférence sur les descriptions, In Actes des journées francophones d'Ingénierie des Connaissances (IC'2000).
  10. Faugeras O., Laveau S., Robert L., Csurka G., Zeller C., Gauclin C. & Zoghlami I., 1997. 3-d reconstruction of urban scenes from image sequences., CVGIP : Image Understanding.
  11. Fleet D. J., Jepson A. D. & Jenkin M. R. M., 1991. PhaseBased Disparity measurement., CVGIP : Image Understanding, 53(2):198-210.
  12. Frasson M., 1999. Reconstruction interactive de scènes tridimensionnelles à partir d'images, M.Sc. Thesis, March.
  13. Grau O., 1997. A Scene Analysis System for the Generation of 3-D Models, 3dim, p. 221, First.
  14. Grimson W. E. L., 1981. From Images to Surfaces., MIT Press.
  15. Grün A., Bär S. & Beutner S., 2002. Signals in the Sand - 3D Recording and Visualization of the Nasca Geoglyphs, PFG (Photogrammetrie, Fernerkundung, Geoinformation), No. 6/2000. pp. 385-398.
  16. Guarino N., 1994, The ontological level, in R. Casati B. S. & White G., eds, Philosophy and the cognitive sciences, Hölder-Pichler-Tempsky.
  17. Guarino N., Carrara C., Giaretta P., 1994. An ontologie of meta-level categories, in J. Doyle F. S & Torano P., eds., Principles of Knowledge representation and Reasonning, Morgan-Kauffman, pages 270-280.
  18. Huot S. & Colin C., 2002. MArINa : reconstruction de bâtiments 3D à partir d'images., Colloque Modélisation Multimodale appliquée à la reconstruction d'environnements architecturaux et urbains, Bordeaux, France.
  19. Jones D. & Malik J., 1992. Computational Framework for determining stereo correspondence from a set of linear spatial filters., Image and Vision Computing, 10(10):699-708, December.
  20. Kuzo P. M., 1999. Des contraintes projectives en modélisation tridimensionnelle interactive, Thèse de doctorat, Ecole des Mines de Nantes - Université de Nantes, novembre.
  21. Loscos C., Frasson M., Drettakis G., Walter B., Granier X. & Poulin P., 1999. Interactive Virtual Relighting and Remodeling of Real Scenes, Proc. Eurographics Workshop on Rendering 99, June.
  22. Marr D. & Poggio T., 1979. A computational theory of human stereo vision. Proceedings of the Royal Society of London, 204:301-328.
  23. McMillan L. & Bishop G., 1995. Plenoptic modeling : An image-based rendering system., In SIGGRAPH 7895.
  24. Nüchter A., Surmann H. & Hertzberg J., 2003. Automatic Model Refinement for 3D Reconstruction with Mobile Robots, Fraunhofer Institute for Autonomous Intelligent Systems (AIS) Schloss Birlinghoven, D53754 Sankt Augustin, Germany.
  25. Pollefeys M., Koch R., Vergauwen M. & Van Gool L. 2000. Automated reconstruction of 3D scenes from sequences of images, ISPRS Journal Of Photogrammetry And Remote Sensing (55)4, pp. 251- 267.
  26. Poulin P., Ouimet M. & M. Frasson, 1998. Interactively Modeling with Photogrammetry, Proc. Eurographics Workshop on Rendering 98, June.
  27. Remondino F., 2003. From point cloud to surface: the modeling and visualization problem, Proc. Int. Worksh. Visualization and Animation of RealityBased 3D Models, Int. Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences XXXIV-5/W10, Feb.
  28. Robert L., 1995. Camera calibration without feature extraction, Computer Vision, Graphics, and Image Processing, 63(2) :314-325, March also INRIA Technical Report 2204.
  29. Weik S. & Grau O., 1996. Recovering 3-D Object Geometry using a Generic Constraint Description. In ISPRS96 - 18th Congress of the International Society for Photogrammetry and Remote Sensing, July, Vienne.
  30. Werner T. & Zisserman A., 2002. New Techniques for Automated Architecture Reconstruction from Photographs, Proc. 7th European Conference on Computer Vision, Copenhagen, Denmark.
  31. Zitova B. & Flusser J., 2003. Image registration methods: A survey, Image and Vision, Computing 21, 977- 1000.
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Paper Citation


in Harvard Style

Cruz C., Marzani F. and Boochs F. (2007). ONTOLOGY-DRIVEN 3D RECONSTRUCTION OF ARCHITECTURAL OBJECTS . In Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 3: 3D Model Aquisition and Representation, (VISAPP 2007) ISBN 978-972-8865-75-7, pages 47-54. DOI: 10.5220/0002047300470054


in Bibtex Style

@conference{3d model aquisition and representation07,
author={Christophe Cruz and Franck Marzani and Frank Boochs},
title={ONTOLOGY-DRIVEN 3D RECONSTRUCTION OF ARCHITECTURAL OBJECTS},
booktitle={Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 3: 3D Model Aquisition and Representation, (VISAPP 2007)},
year={2007},
pages={47-54},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002047300470054},
isbn={978-972-8865-75-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 3: 3D Model Aquisition and Representation, (VISAPP 2007)
TI - ONTOLOGY-DRIVEN 3D RECONSTRUCTION OF ARCHITECTURAL OBJECTS
SN - 978-972-8865-75-7
AU - Cruz C.
AU - Marzani F.
AU - Boochs F.
PY - 2007
SP - 47
EP - 54
DO - 10.5220/0002047300470054