Stochastic mesh-based multiview reconstruction

A method for reconstruction of 3D polygonal models from multiple views is presented. The method uses sampling techniques to construct a texture-mapped semiregular polygonal mesh of the object in question. Given a set of views and segmentation of the object in each view, constructive solid geometry is used to build a visual hull from silhouette prisms. The resulting polygonal mesh is simplified and subdivided to produce a semiregular mesh. Regions of model fit inaccuracy are found by projecting the reference images onto the mesh from different views. The resulting error images for each view are used to compute a probability density function, and several points are sampled from it. Along the epipolar lines corresponding to these sampled points, photometric consistency is evaluated. The mesh surface is then pulled towards the regions of higher photometric consistency using free-form deformations. This sampling-based approach produces a photometrically consistent solution in much less time than possible with previous multi-view algorithms given arbitrary camera placement.

[1]  Kiriakos N. Kutulakos,et al.  A Theory of Shape by Space Carving , 2000, International Journal of Computer Vision.

[2]  Dimitris N. Metaxas,et al.  Dynamic 3D Models with Local and Global Deformations: Deformable Superquadrics , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Thomas Malzbender,et al.  Generalized Voxel Coloring , 1999, Workshop on Vision Algorithms.

[4]  Richard Szeliski,et al.  Real-Time Octree Generation from Rotating Objects , 1990 .

[5]  Kiriakos N. Kutulakos.  Approximate N-View Stereo , 2000, ECCV.

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

[7]  Yang Chen,et al.  Fitting a surface to 3-D points using an inflating balloon model , 1994, Proceedings of 1994 IEEE 2nd CAD-Based Vision Workshop.

[8]  Paul A. Viola,et al.  Roxels: responsibility weighted 3D volume reconstruction , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[9]  David H. Douglas,et al.  ALGORITHMS FOR THE REDUCTION OF THE NUMBER OF POINTS REQUIRED TO REPRESENT A DIGITIZED LINE OR ITS CARICATURE , 1973 .

[10]  R. Zabih,et al.  Exact voxel occupancy with graph cuts , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[11]  Li Zhang,et al.  Latex2e Cmu-techreport Image-based Multiresolution Modeling by Surface Deformation , 2000 .

[12]  Thomas Malzbender,et al.  Improved Voxel Coloring Via Volumetric Optimization , 2001 .

[13]  Andrew W. Fitzgibbon,et al.  Automatic 3D Model Construction for Turn-Table Sequences , 1998, SMILE.

[14]  Michael Garland,et al.  Surface simplification using quadric error metrics , 1997, SIGGRAPH.

[15]  Steven M. Seitz,et al.  Photorealistic Scene Reconstruction by Voxel Coloring , 1997, International Journal of Computer Vision.

[16]  Ramesh Raskar,et al.  Image-based visual hulls , 2000, SIGGRAPH.

[17]  R. Cipolla,et al.  A probabilistic framework for space carving , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[18]  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.

[19]  Peter Eisert,et al.  3-D reconstruction of real-world objects using extended voxels , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).