The Visual Computer

, Volume 32, Issue 6–8, pp 955–965 | Cite as

Texture map generation for 3D reconstructed scenes

  • Junho Jeon
  • Yeongyu Jung
  • Haejoon Kim
  • Seungyong LeeEmail author
Original Article


We present a novel method for generating texture maps for 3D geometric models reconstructed using consumer RGB-D sensors. Our method generates a texture map for a simplified 3D mesh of the reconstructed scene using spatially and temporally sub-sampled key frames of the input RGB stream. We acquire an accurate texture map by optimizing the texture coordinates of the 3D model to maximize the photometric consistency among multiple key frames. We show that the optimization can be performed efficiently using GPU by exploiting the locality of texture coordinate manipulation. Experimental results demonstrate that our method can generate a texture map in a few tens of seconds for a large 3D model, such as a whole room.


3D reconstruction Texture mapping RGB-D images  Photometric consistency optimization 



This work was supported by the National Research Foundation of Korea (NRF) Grant (NRF-2014R1A2A1A11052779) and Institute for Information and Communications Technology Promotion (IITP) Grant (R0126-16-1078), both funded by the Korea government (MSIP).

Supplementary material

Supplementary material 1 (wmv 142766 KB)


  1. 1.
    Agarwal, S., Furukawa, Y., Snavely, N., Simon, I., Curless, B., Seitz, S.M., Szeliski, R.: Building rome in a day. Commun. ACM 54(10), 105–112 (2011)CrossRefGoogle Scholar
  2. 2.
    Blender foundation: blender. Accessed Jan 2016
  3. 3.
    Cignoni, P., Corsini, M., Ranzuglia, G.: MeshLab: an open-source 3D mesh processing system. Ercim News 73(45–46), 6 (2008)Google Scholar
  4. 4.
    Crandall, D., Owens, A., Snavely, N., Huttenlocher, D.: Discrete-continuous optimization for large-scale structure from motion. In: 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3001–3008. IEEE (2011)Google Scholar
  5. 5.
    Crété-Roffet, F., Dolmiere, T., Ladret, P., Nicolas, M.: The blur effect: perception and estimation with a new no-reference perceptual blur metric. In: SPIE Electronic Imaging Symposium Conf Human Vision and Electronic Imaging, vol. 12, pp. EI–6492 (2007)Google Scholar
  6. 6.
    Garland, M., Heckbert, P.S.: Surface simplification using quadric error metrics. In: Proceedings of the 24th Annual Conference on Computer Graphics and Interactive Techniques, pp. 209–216. ACM Press/Addison-Wesley Publishing Co., New York (1997)Google Scholar
  7. 7.
    Hazewinkel, M. (ed.): Encyclopaedia of Mathematics (Set). Springer, The Netherlands (1994)zbMATHGoogle Scholar
  8. 8.
    Lévy, B., Petitjean, S., Ray, N., Maillot, J.: Least squares conformal maps for automatic texture atlas generation. ACM Trans. Graph. (TOG) 21(3), 362–371 (2002)CrossRefGoogle Scholar
  9. 9.
    Liu, L., Zhang, L., Xu, Y., Gotsman, C., Gortler, S.J.: A local/global approach to mesh parameterization. In: Computer Graphics Forum, vol. 27, pp. 1495–1504. Wiley Online Library, New York (2008)Google Scholar
  10. 10.
    Newcombe, R.A., Izadi, S., Hilliges, O., Molyneaux, D., Kim, D., Davison, A.J., Kohi, P., Shotton, J., Hodges, S., Fitzgibbon, A.: Kinectfusion: real-time dense surface mapping and tracking. In: 2011 10th IEEE International Symposium on Mixed and Augmented Reality (ISMAR), pp. 127–136. IEEE (2011)Google Scholar
  11. 11.
    Niener, M., Zollhfer, M., Izadi, S., Stamminger, M.: Real-time 3D reconstruction at scale using voxel hashing. ACM Trans. Graph. (TOG) 32(6), 169 (2013)Google Scholar
  12. 12.
    Roth, H., Vona, M.: Moving volume kinectfusion. In: BMVC, pp. 1–11 (2012)Google Scholar
  13. 13.
    Smith, J., Schaefer, S.: Bijective parameterization with free boundaries. ACM Trans. Graph. (TOG) 34(4), 70 (2015)CrossRefzbMATHGoogle Scholar
  14. 14.
    Tomasi, C., Kanade, T.: Shape and motion from image streams under orthography: a factorization method. Int. J. Comput. Vis. 9(2), 137–154 (1992)CrossRefGoogle Scholar
  15. 15.
    Whelan, T., Johannsson, H., Kaess, M., Leonard, J.J., McDonald, J.: Robust tracking for real-time dense rgb-d mapping with kintinuous. Technical Report MIT-CSAIL-TR-2012-031, CSAIL, MIT (2012)Google Scholar
  16. 16.
    Zhou, Q.Y., Koltun, V.: Dense scene reconstruction with points of interest. ACM Trans. Graph. (TOG) 32(4), 112 (2013)zbMATHGoogle Scholar
  17. 17.
    Zhou, Q.Y., Koltun, V.: Color map optimization for 3D reconstruction with consumer depth cameras. ACM Trans. Graph. (TOG) 33(4), 155 (2014)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Junho Jeon
    • 1
  • Yeongyu Jung
    • 1
  • Haejoon Kim
    • 1
  • Seungyong Lee
    • 1
    Email author
  1. 1.Department of Computer Science and EngineeringPOSTECHPohangKorea

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