AN ACTIVE STEREOSCOPIC SYSTEM FOR ITERATIVE 3D SURFACE RECONSTRUCTION

Wanjing Li, Franck S. Marzani, Yvon Voisin, Frank Boochs

Abstract

For most traditional active 3D surface reconstruction methods, a common feature is that the object surface is scanned uniformly, so that the final 3D model contains a very large number of points, which requires huge storage space, and makes the transmission and visualization time-consuming. A post-process then is necessary to reduce the data by decimation. In this paper, we present a newly active stereoscopic system based on iterative spot pattern projection. The 3D surface reconstruction process begins with a regular spot pattern, and then the pattern is modified progressively according to the object’s surface geometry. The adaptation is controlled by the estimation of the local surface curvature of the actual reconstructed 3D surface. The reconstructed 3D model is optimized: it retains all the morphological information about the object with a minimal number of points. Therefore, it requires little storage space, and no further mesh simplification is needed.

References

  1. Alboul, L., Echeverria G., Rodrigues, M., 2005. Discrete curvatures and gauss maps for polyhedral surfaces, in European Workshop on Computational Geometry (EWCG), Eindhoven, the Netherlands, pp. 69-72.
  2. Battle, J., Mouaddib, E., Salvi, J., 1998. Recent progress in coded structured light as a technique to solve the correspondence Problem: a Survey, Pattern Recognition, 31(7), pp. 963-982.
  3. Böhler, M., Boochs, F., 2006. Getting 3D shapes by means of projection and photogrammetry, Inspect, GITVerlag, Darmstadt.
  4. Dyn, N., Hormann, K., Kim S. J., Levin, D., 2001. Optimizing 3D triangulations using discrete curvature analysis, Mathematical Methods for Curves and Surfaces, Oslo 2000, Nashville, TN, pp.135-146.
  5. Faugeras, O. D., Toscani, G., 1986. The calibration problem for stereo, in Proc. Computer Vision and Pattern Recognition, Miami Beach, Florida, USA, pp.15-20.
  6. Garcia, D., Orteu, J.J., Devy, M., 2000. Accurate Calibration of a Stereovision Sensor: Comparison of Different Approaches, 5th Workshop on Vision Modeling and Visualization (VMV'2000), Saarbrücken, Germany, pp.25-32.
  7. Grün, A., Beyer, H., 1992. System calibration through self-calibration, Workshop on Calibration and Orientation of Cameras in Computer Vision, Washington D.C..
  8. Horaud, R., Monga, O., 1995. Vision par ordinateur: outils fondamentaux, Hermès, 2nd edition.
  9. Isenburg, M., Lindstrom, P., Gumhold, S., Snoeyink, J., 2003. Large mesh simplification using processing sequences, in Proc. Visualization'03, pp. 465-472.
  10. Kanaganathan, S., Goldstein, N.B., 1991. Comparison of four point adding algorithms for Delaunay type three dimensional mesh generators, IEEE Transactions on magnetics, 27(3).
  11. Krattenthaler, W., Mayer, K.J., Duwe, H.P., 1994. 3Dsurface measurement with coded light approach, In Proc. of the 17th meeting of the Austrian Association for Pattern Recognition on Image Analysis and Synthesis, pp. 103-114.
  12. Lathuilière, A., Marzani, F., Voisin, Y., 2003. Calibration of a LCD projector with pinhole model in active stereovision applications. Conference SPIE :Two- and Three-Dimensional Vision Systems for Inspection, Control, and Metrology, Rhode Island, USA, 5265, pp. 199-204.
  13. Legarda-Saenz, R., Bothe, T., Jüptner, W.P., 2004. Accurate Procedure for the Calibration of a Structured Light System, Optical Engineering, 43(2), pp.464- 471.
  14. Li, W., Boochs, F., Marzani, F., Voisin, Y., 2006. Iterative 3D surface reconstruction with adaptive Pattern projection, in Proc. of the Sixth IASTED International Conference on Visulatization, Imaging and Image Processing (VIIP), Palma De Mallorca, Spain, pp.336-341.
  15. Marzani, F., Voisin, Y., Diou, A., Lew Yan Voon, L.F.C., 2002. Calibration of a 3D reconstruction system using a structured light source, Journal of Optical Engineering, 41 (2), pp. 484-492.
  16. Peng, J., Li, Q., Jay kuo C.C., Zhou, M., 2003. Estimating Gaussian Curvatures from 3D meshes. SPIE Electronic Image, vol.5007, pp. 270-280.
  17. Surazhsky, T., Magid, E., Soldea, O., Elber, G., Rivlin, E., 2003. A comparison of gaussian and mean curvatures estimation methods on triangular meshes, in IEEE International Conference on Robotics & Automation.
  18. Tsai, R.Y., 1986. An efficient and accurate camera calibration technique for 3D machine vision, IEEE Computer Vision and Pattern Recognition, Miami Beach Florida, pp.364-374.
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Paper Citation


in Harvard Style

Li W., S. Marzani F., Voisin Y. and Boochs F. (2007). AN ACTIVE STEREOSCOPIC SYSTEM FOR ITERATIVE 3D SURFACE RECONSTRUCTION . 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 78-84. DOI: 10.5220/0002065500780084


in Bibtex Style

@conference{3d model aquisition and representation07,
author={Wanjing Li and Franck S. Marzani and Yvon Voisin and Frank Boochs},
title={AN ACTIVE STEREOSCOPIC SYSTEM FOR ITERATIVE 3D SURFACE RECONSTRUCTION},
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={78-84},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002065500780084},
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 - AN ACTIVE STEREOSCOPIC SYSTEM FOR ITERATIVE 3D SURFACE RECONSTRUCTION
SN - 978-972-8865-75-7
AU - Li W.
AU - S. Marzani F.
AU - Voisin Y.
AU - Boochs F.
PY - 2007
SP - 78
EP - 84
DO - 10.5220/0002065500780084