3D scene representation using a deformable surface

This paper presents a method based on a deformable surface (DS) for constructing representations of real 3D scenes from multiple range images. The DS model uses physically based surface and edge constraints to reconstruct a representation from noisy 3D data. The representation constructed identifies consistent surface regions and discontinuities which fit the 3D data to within known tolerances. Fusion of multiple range images enables a complete 3D scene reconstruction. A multi-scale representation is obtained which gives an order of magnitude data reduction. Representations can be used for feature matching or CAD model building

[1]  M. Isabel Ribeiro,et al.  3D environment modelling using laser range sensing , 1995, Robotics Auton. Syst..

[2]  Paul J. Besl,et al.  Surfaces in Range Image Understanding , 1988, Springer Series in Perception Engineering.

[3]  Marc Levoy,et al.  Zippered polygon meshes from range images , 1994, SIGGRAPH.

[4]  Dimitris N. Metaxas,et al.  Dynamic 3D models with local and global deformations: deformable superquadrics , 1990, [1990] Proceedings Third International Conference on Computer Vision.

[5]  Demetri Terzopoulos,et al.  The Computation of Visible-Surface Representations , 1988, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  ISAAC COHEN,et al.  Using deformable surfaces to segment 3-D images and infer differential structures , 1992, CVGIP Image Underst..

[7]  Gérard G. Medioni,et al.  Object modeling by registration of multiple range images , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[8]  Adrian Hilton,et al.  SLIME: A new deformable surface , 1994, BMVC.

[9]  Andrew P. Witkin,et al.  Free-form shape design using triangulated surfaces , 1994, SIGGRAPH.

[10]  Andrew Blake,et al.  Visual Reconstruction , 1987, Deep Learning for EEG-Based Brain–Computer Interfaces.

[11]  Alex Pentland,et al.  Closed-form solutions for physically-based shape modeling and recognition , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[12]  Steven W. Zucker,et al.  The Local Structure of Image Discontinuities in One Dimension , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[13]  Hervé Delingette,et al.  Simplex meshes: a general representation for 3D shape reconstruction , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[14]  Xin Chen,et al.  Vision-based construction of CAD models from range images , 1993, 1993 (4th) International Conference on Computer Vision.

[15]  Claus B. Madsen,et al.  Experiments in mobile robot navigation and range imaging , 1993 .

[16]  Demetri Terzopoulos,et al.  Regularization of Inverse Visual Problems Involving Discontinuities , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[17]  Demetri Terzopoulos,et al.  A finite element model for 3D shape reconstruction and nonrigid motion tracking , 1993, 1993 (4th) International Conference on Computer Vision.

[18]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[19]  Gérard G. Medioni,et al.  Object modelling by registration of multiple range images , 1992, Image Vis. Comput..

[20]  Ruzena Bajcsy,et al.  Integrated approach for surface and volumetric segmentation of range images using biquadrics and superquadrics , 1992, Defense, Security, and Sensing.

[21]  Charles T. Loop.  A G1 triangular spline surface of arbitrary topological type , 1994, Comput. Aided Geom. Des..