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

Authors:
Wanjing Li;Martin Böhler;Rainer Schütze;Franck. S. Marzani;Yvon Voisin;Frank Boochs
Affiliations:
Laboratory Le2i, Building Mirande, UFR Sc. & Tech, Dijon Cedex, France 21078 and Laboratory i3Mainz, University of Applied Sciences, Mainz, Germany 55116;Laboratory i3Mainz, University of Applied Sciences, Mainz, Germany 55116;Laboratory i3Mainz, University of Applied Sciences, Mainz, Germany 55116;Laboratory Le2i, Building Mirande, UFR Sc. & Tech, Dijon Cedex, France 21078;Laboratory Le2i, Route des Plaines de l'Yonne, Auxerre Cedex, France 89010;Laboratory i3Mainz, University of Applied Sciences, Mainz, Germany 55116
Venue:
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
Year:
2008

Citing 2
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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.