3D modelling of facade features on large sites acquired by vehicle based laser scanning

• Autorzy: Boulaassal H. , Landes T. , Grussenmeyer P.
• Języki publikacji: EN

Abstrakty

EN

Mobile mapping laser scanning systems have become more and more widespread for the acquisition of millions of 3D points on large and geometrically complex urban sites. Vehicle-based Laser Scanning (VLS) systems travel many kilometers while acquiring raw point clouds which are registered in real time in a common coordinate system. Improvements of the acquisition steps as well as the automatic processing of the collected point clouds are still a conundrum for researchers. This paper shows some results obtained by application, on mobile laser scanner data, of segmentation and reconstruction algorithms intended initially to generate individual vector facade models using stationary Terrestrial Laser Scanner (TLS) data. The operating algorithms are adapted so as to take into account characteristics of VLS data. The intrinsic geometry of a point cloud as well as the relative geometry between registered point clouds are different from that obtained by a static TLS. The amount of data provided by this acquisition technique is another issue. Such particularities should be taken into consideration while processing this type of point clouds. The segmentation of VLS data is carried out based on an adaptation of RANSAC algorithm. Edge points of each element are extracted by applying a second algorithm. Afterwards, the vector models of each facade element are reconstructed. In order to validate the results, large samples with different characteristics have been introduced in the developed processing chain. The limitations as well as the capabilities of each process will be emphasized in terms of geometry and processing time.

Słowa kluczowe

EN

VLS; point cloud; segmentation; reconstruction; mobile mapping; building facade

PL

VLS; chmura punktów; segmentacja; rekonstrukcja; mobile mapping; elewacja kamienicy

• Wydawca: Zarząd Główny Stowarzyszenia Geodetów Polskich
• Czasopismo: Archiwum Fotogrametrii, Kartografii i Teledetekcji
• Rocznik: 2011
• Tom: Vol. 22
• Strony: 75--89
• Opis fizyczny: Bibliogr. 16 poz.

Twórcy

autor

Boulaassal H.

• The Image Sciences, Computer Sciences and Remote Sensing Laboratory Photogrammetry and Geomatics Group, INSA Strasbourg 24, Boulevard de la Victoire 67084, Strasbourg, France

autor

Landes T.

• The Image Sciences, Computer Sciences and Remote Sensing Laboratory Photogrammetry and Geomatics Group, INSA Strasbourg 24, Boulevard de la Victoire 67084 Strasbourg, France

autor

Grussenmeyer P.

• The Image Sciences, Computer Sciences and Remote Sensing Laboratory Photogrammetry and Geomatics Group, INSA Strasbourg 24, Boulevard de la Victoire 67084 Strasbourg, France

Bibliografia

• 1. Alshawa, M., Boulaassal, H., Landes, T., Grussenmeyer, P., 2009. Acquisition and automatic extraction of facade elements on large sites from a low cost laser mobile mapping system. 3D-ARCH’2009. 3D Virtual Modelling and Visualization of Complex Architectures 25-28 February 2009, Trento, Italy. Volume XXXVIII-5/W1 ISSN p 1682-1777
• 2. Amenta, N., Choi, S., Dey, T., Leekha, N., 2002. A simple algorithm for homeomorphic surface reconstruction. International journal of Computational Geometry and its Applications 12(1-2), pp. 213-222.
• 3. Boulaassal, H., Chevrier, C., Landes, T., 2010. From Laser Data to Parametric Models: Towards an Automatic Method for Building Facade Modelling. EuroMed 2010, Lecture Notes in Computer Science. Springer-Verlag Berlin Heidelberg 2010, pp. 42–55.
• 4. Budroni, A., Bohm, J., 2009. Automatic reconstruction of interiors from laser data. 3DARCH’2009. 3D Virtual Modelling and Visualization of Complex Architectures 25-28 February 2009, Trento, Italy.
• 5. Conforti, D., Zampa, F., 2011. Lynx mobile mapper for surveying city centers and highways. Proceedings of the 4 th ISPRS International Workshop. (3D-ARCH 2011). 3D Virtual Reconstruction and Visualization of Complex Architectures. Trento, Italy, 2-4 March 2011.
• 6. Frueh. C., Jain, S., Zakhor, V. 2005. Data Processing Algorithms for Generating Textured 3D Building Façade Meshes from Laser Scans and Camera Images. International Journal of Computer Vision 61(2), 159–184, 2005. Copyright, 2005 Springer Science + Business Media, Inc. Manufactured in The Netherlands.
• 7. Haala, N., Peter, M., Cefalu, A., Kremer, J., 2008. Mobile lidar mapping for urban data capture. VSMM 2008 - Conference on Virtual Systems and MultiMedia Dedicated to Digital Heritage. Limassol, Cyprus, October 20th - 25th, 2008. Project paper. pp. 101-106.
• 8. Hartley, R., Zisserman,A., 2003. Multiple View Geometry in Computer Vision. pp. 117–121. Cambridge University Press, second edition 2003.
• 9. Henricsson, O. and Baltsavias, E., 1997. 3-D building reconstruction with ARUBA: a qualitative and quantitative evaluation. Proceedings of the international Workshop on Automatic Extraction of Man-Made Objects from Aerial and Space Images (II), Ascona, Swizerland. 12 pages.
• 10. Landes, T., Boulaassal, H., Grussenmeyer, P., 2012. Quality assessment of geometric façade models reconstructed from TLS Data. The Photogrammetric Record (to be published).
• 11. McGlone, J. C. and Shufelt, J. A., 1994. Projective and object space geometry for monocular building extraction. Proceedings of Computer Vision and Pattern Recognition, Seattle, USA. 7 pages.
• 12. Schmitt, A.; Vögtle, T., 2009. An advanced approach for automatic extraction of plan ar surfaces and their topology from point clouds. Photogrammetrie, Fernerkundung und Geoinformation 2009, 1, 43–52.
• 13. Schuster, H. F. and Weidner, U., 2003. A new approach towards quantitative quality evaluation of 3D building models. ISPRS Commission IV Joint Workshop on Challenges in Geospatial Analysis, Integration and Visualization II, Stuttgart, Germany. 8 pages
• 14. Tao, C., V., Li, J., 2007. Advances in mobile mapping technology. ISPRS Book Series Volume 4, © 2007 Taylor & Francis Group, London.
• 15. Tarsha-Kurdi, F., Landes, T., Grussenmeyer, P., 2007. Hough-transform and extender RANSAC algorithms for automatic detection of 3D building roof planes from LIDAR data. International Archives of Photogrammetry, Remote Sensing and Spatial Information Systems. vol. XXXVI, Part 3 /W52, 2007, pp. 407-412.
• 16. Yu, G., Grossberg, M., Wolberg, G., Stamos, I., 2008. Think globbaly, cluster locally: a unified framework for range segmentation. Proceedings of 3DPVT’08-the Fourth Symposium on 3D Data Processing, Visualization and Transmission. 8 pages.