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User Driven 3D Reconstruction Environment

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Advances in Visual Computing (ISVC 2012)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7431))

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Abstract

An intuitive image-based 3D reconstruction tool based on inaccurate user strokes is presented in this paper. The combination of fast image segmentation method together with user knowledge about reconstructed scene forms a novel low-polygonal editor suitable for architecture reconstruction. The user interaction is minimized thanks to propagation of strokes among input photographs. The final model geometry is created by innovative algorithm. The input to the tool is a set of calibrated photographs together with a sparse pointcloud. The output is a structured low-poly 3D model.

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References

  1. Snavely, N., Seitz, S.M., Szeliski, R.: Photo tourism: exploring photo collections in 3d. In: SIGGRAPH 2006: ACM SIGGRAPH 2006 Papers, pp. 835–846. ACM, New York (2006)

    Chapter  Google Scholar 

  2. Deseilligny, M.P., Clery, I.: Apero, an open source bundle adjusment software for automatic calibration and orientation of set of images. In: Proceedings of the ISPRS Symposium, 3DARCH11 2011 (2011)

    Google Scholar 

  3. Debevec, P.E., Taylor, C.J., Malik, J.: Modeling and rendering architecture from photographs: a hybrid geometry- and image-based approach. In: SIGGRAPH 1996: Proceedings of the 23rd Annual Conference on Computer Graphics and Interactive Techniques, pp. 11–20. ACM, New York (1996)

    Chapter  Google Scholar 

  4. van den Hengel, A., Dick, A., Thormählen, T., Ward, B., Torr, P.H.S.: Videotrace: rapid interactive scene modelling from video. In: SIGGRAPH 2007: ACM SIGGRAPH 2007 Papers, p. 86. ACM, New York (2007)

    Chapter  Google Scholar 

  5. Sinha, S.N., Steedly, D., Szeliski, R., Agrawala, M., Pollefeys, M.: Interactive 3d architectural modeling from unordered photo collections. In: SIGGRAPH Asia 2008: ACM SIGGRAPH Asia 2008 Papers, pp. 1–10. ACM, New York (2008)

    Google Scholar 

  6. Habbecke, M., Kobbelt, L.: An intuitive interface for interactive high quality image-based modeling. Comput. Graph. Forum 28, 1765–1772 (2009)

    Article  Google Scholar 

  7. Paczkowski, P., Kim, M.H., Morvan, Y., Dorsey, J., Rushmeier, H., O’Sullivan, C.: Insitu: sketching architectural designs in context. ACM Trans. Graph. 30, 182:1–182:10 (2011)

    Article  Google Scholar 

  8. Jiang, N., Tan, P., Cheong, L.F.: Symmetric architecture modeling with a single image. In: SIGGRAPH Asia 2009: ACM SIGGRAPH Asia 2009 Papers, pp. 1–8. ACM, New York (2009)

    Chapter  Google Scholar 

  9. Guillaume, L.Z., Zhang, L., Dugas-phocion, G.: Single view modeling of free-form scenes. In: Proc. of CVPR, pp. 990–997 (2002)

    Google Scholar 

  10. Zheng, Y., Chen, X., Cheng, M.M., Zhou, K., Hu, S.M., Mitra, N.J.: Interactive images: Cuboid proxies for smart image manipulation. ACM Transactions on Graphics 31 (2012)

    Google Scholar 

  11. Duan, W., Allinson, N.M.: Vanishing points detection and line grouping for complex building facade. In: Proc. of WSCG 2010 (2010)

    Google Scholar 

  12. Cipolla, R., Robertson, D.: 3d models of architectural scenes from uncalibrated images and vanishing points. In: Proceedings. International Conference on Image Analysis and Processing, pp. 824–829 (1999)

    Google Scholar 

  13. Wilczkowiak, M., Sturm, P., Boyer, E.: Using geometric constraints through parallelepipeds for calibration and 3d modeling. IEEE Transactions on Pattern Analysis and Machine Intelligence 27, 194–207 (2005)

    Article  Google Scholar 

  14. El-hakim, S., Whiting, E., Gonzo, L.: 3d modelling with reusable and integrated building blocks. In: 7th Conference on Optical 3-D Measurement Techniques, pp. 3–5 (2005)

    Google Scholar 

  15. Xiao, J., Fang, T., Tan, P., Zhao, P., Ofek, E., Quan, L.: Image-based façade modeling. In: SIGGRAPH Asia 2008: ACM SIGGRAPH Asia 2008 Papers, pp. 1–10. ACM, New York (2008)

    Google Scholar 

  16. Jorge, J., Samavati, F.F. (eds.): Sketch-based Interfaces and Modeling, 1st edn. Springer (2011)

    Google Scholar 

  17. Boykov, Y., Veksler, O., Zabih, R.: Fast approximate energy minimization via graph cuts. IEEE Trans. Pattern Anal. Mach. Intell. 23, 1222–1239 (2001)

    Article  Google Scholar 

  18. Sýkora, D., Dingliana, J., Collins, S.: Lazybrush: Flexible painting tool for hand-drawn cartoons. In: Computer Graphics Forum (Proceedings of Eurographics 2009), vol. 28, pp. 599–608 (2009)

    Google Scholar 

  19. Boykov, Y., Veksler, O., Zabih, R.: Markov random fields with efficient approximations. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 1998, p. 648. IEEE Computer Society Press, Washington, DC (1998)

    Google Scholar 

  20. Lombaert, H., Sun, Y., Grady, L., Xu, C.: A multilevel banded graph cuts method for fast image segmentation. In: Tenth IEEE International Conference on Computer Vision, ICCV 2005, vol. 1, pp. 259–265 (2005)

    Google Scholar 

  21. Jamriška, O., Sýkora, D., Hornung, A.: Cache-efficient graph cuts on structured grids. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (2012)

    Google Scholar 

  22. Fischler, M.A., Bolles, R.C.: Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Communications of the ACM 24, 381–395 (1981)

    Article  MathSciNet  Google Scholar 

  23. Schnabel, R., Wahl, R., Klein, R.: Efficient ransac for point-cloud shape detection. Computer Graphics Forum 26, 214–226 (2007)

    Article  Google Scholar 

  24. Bernstein, G., Fussell, D.: Fast, exact, linear booleans. In: Proceedings of the Symposium on Geometry Processing, SGP 2009, Aire-la-Ville, Switzerland, Eurographics Association, pp. 1269–1278 (2009)

    Google Scholar 

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Sedlacek, D., Zara, J. (2012). User Driven 3D Reconstruction Environment. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2012. Lecture Notes in Computer Science, vol 7431. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33179-4_11

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  • DOI: https://doi.org/10.1007/978-3-642-33179-4_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33178-7

  • Online ISBN: 978-3-642-33179-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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