Dealing with textureless regions and specular highlights - a progressive space carving scheme using a novel photo-consistency measure

We present two extensions to the space carving framework. The first is a progressive scheme to better reconstruct surfaces lacking sufficient textures. The second is a novel photo-consistency measure that is valid for both specular and diffuse surfaces, under unknown lighting conditions.

[1]  Stephen Lin,et al.  Multibaseline stereo in the presence of specular reflections , 2002, Object recognition supported by user interaction for service robots.

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

[3]  Jean Ponce,et al.  Computer Vision: A Modern Approach , 2002 .

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

[5]  Ruigang Yang,et al.  Eye gaze correction with stereovision for video-teleconferencing , 2002, IEEE Transactions on Pattern Analysis and Machine Intelligence.

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

[7]  C. Dyer.  Volumetric Scene Reconstruction from Multiple Views , 2001 .

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

[9]  Kiriakos N. Kutulakos,et al.  A Probabilistic Theory of Occupancy and Emptiness , 2002, ECCV.

[10]  David J. Kriegman,et al.  Beyond Lambert: reconstructing surfaces with arbitrary BRDFs , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[11]  B. Julesz,et al.  A disparity gradient limit for binocular fusion. , 1980, Science.

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

[13]  Bui Tuong Phong.  Illumination for computer generated pictures , 1975, Commun. ACM.

[14]  Larry S. Davis,et al.  A probabilistic framework for surface reconstruction from multiple images , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

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

[16]  M. J. D. Powell,et al.  A fast algorithm for nonlinearly constrained optimization calculations , 1978 .

[17]  Zhengyou Zhang,et al.  A Progressive Scheme for Stereo Matching , 2000, SMILE.

[18]  Jeremy S. De Bonet,et al.  Poxels: Probabilistic Voxelized Volume Reconstruction , 1999 .

[19]  Stefano Soatto,et al.  Variational multiframe stereo in the presence of specular reflections , 2002, Proceedings. First International Symposium on 3D Data Processing Visualization and Transmission.

[20]  Ruigang Yang,et al.  View-Dependent Pixel Coloring-A Physically-Based Approach for 2 D View Synthesis , 2003 .

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

[22]  Kiriakos N. Kutulakos,et al.  Multi-view scene capture by surfel sampling: from video streams to non-rigid 3D motion, shape and reflectance , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[23]  Vladimir Kolmogorov,et al.  Multi-camera Scene Reconstruction via Graph Cuts , 2002, ECCV.

[24]  Shree K. Nayar,et al.  Stereo in the presence of specular reflection , 1995, Proceedings of IEEE International Conference on Computer Vision.

[25]  J. Mayhew,et al.  Disparity Gradient, Lipschitz Continuity, and Computing Binocular Correspondences , 1985 .

[26]  Thomas Malzbender,et al.  A Survey of Methods for Volumetric Scene Reconstruction from Photographs , 2001, VG.

[27]  Stephen Lin,et al.  Diffuse-Specular Separation and Depth Recovery from Image Sequences , 2002, ECCV.

[28]  Vikram Chhabra.  Reconstructing specular objects with Image Based Rendering using Color Caching , 2001 .