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Use of Local Surface Curvature Estimation for Adaptive Vision System Based on Active Light Projection

  • Wanjing Li
  • Martin Böhler
  • Rainer Schütze
  • Franck. S. Marzani
  • Yvon Voisin
  • Frank Boochs
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5259)

Abstract

In this paper, we present a new 3D reconstruction approach based on local surface curvature analysis. Its integration can make a normal active stereoscopic system intelligent, and capable to produce directly optimized 3D model. The iterative 3D reconstruction process begins with a sparse and regular point pattern. Based on the reconstructed 3D point cloud, the local surface curvature around each 3D point is estimated. Those 3D points located in flat areas are removed from the 3D model, and a new pattern is created to project more points onto the object where there is high surface curvature. The 3D model is thus refined progressively during the acquisition process, and finally an optimized 3D model is obtained. Our numerous experiments showed that compared to the 3D models generated by commercial system, the loss of morphological quality is negligible, and the gain by the simplification of the model is considerable.

Keywords

Gaussian Curvature Camera Calibration Pattern Point Mesh Simplification Local Surface Curvature 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Wanjing Li
    • 1
    • 2
  • Martin Böhler
    • 2
  • Rainer Schütze
    • 2
  • Franck. S. Marzani
    • 1
  • Yvon Voisin
    • 3
  • Frank Boochs
    • 2
  1. 1.Laboratory Le2i, Building MirandeUFR Sc. & TechDijon CedexFrance
  2. 2.Laboratory i3MainzUniversity of Applied SciencesMainzGermany
  3. 3.Laboratory Le2i, Route des Plaines de l’YonneAuxerre CedexFrance

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