An improved PMVS through scene geometric information

Multi-view based reconstruction is one of the central problems in computer vision.In recent years,many excellent algorithms have been reported,such as the PMVS by Furukawa.However,we observed that the following two aspects of the PMVS need further improvements.The first one is that the obtained normal of reconstructed point is not well consistent with its local geometry,and the problem becomes more pronounced under certain image capturing configuration such as downward-shooting or upward-shooting,a frequent practice in large scene reconstruction.The second is its inherent space and time complexity.Especially with high resolution images,its space and time loads become una?ordable.In this work,two remedies are proposed.We propose a patch adjusting trick through the scene geometric information to enhance the patch s normal estimation,and a multi-resolution expanding tactic to well balance the computational cost and the reconstruction accuracy.The experiments demonstrate the e?ectiveness and practicability of our improved algorithm.

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

[2]  Francis Schmitt,et al.  Silhouette and stereo fusion for 3D object modeling , 2003, Fourth International Conference on 3-D Digital Imaging and Modeling, 2003. 3DIM 2003. Proceedings..

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

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

[5]  Pau Gargallo,et al.  Bayesian 3D modeling from images using multiple depth maps , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[6]  Long Quan,et al.  A quasi-dense approach to surface reconstruction from uncalibrated images , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[7]  Long Quan,et al.  A Surface Reconstruction Method Using Global Graph Cut Optimization , 2006, International Journal of Computer Vision.

[8]  Leif Kobbelt,et al.  Hierarchical Volumetric Multi-view Stereo Reconstruction of Manifold Surfaces based on Dual Graph Embedding , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[9]  Michael M. Kazhdan,et al.  Poisson surface reconstruction , 2006, SGP '06.

[10]  Larry S. Davis,et al.  3D Surface Reconstruction Using Graph Cuts with Surface Constraints , 2006, ECCV.

[11]  Steven M. Seitz,et al.  Photo tourism: exploring photo collections in 3D , 2006, ACM Trans. Graph..

[12]  Michael Goesele,et al.  Multi-View Stereo Revisited , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[13]  Luc Van Gool,et al.  Combined Depth and Outlier Estimation in Multi-View Stereo , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[14]  Radu Horaud,et al.  TransforMesh : A Topology-Adaptive Mesh-Based Approach to Surface Evolution , 2007, ACCV.

[15]  Derek Bradley,et al.  Accurate multi-view reconstruction using robust binocular stereo and surface meshing , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[16]  Jean Ponce,et al.  Carved Visual Hulls for Image-Based Modeling , 2006, International Journal of Computer Vision.

[17]  Jean-Philippe Pons,et al.  Towards high-resolution large-scale multi-view stereo , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[18]  Richard Szeliski,et al.  Manhattan-world stereo , 2009, CVPR.

[19]  Jean Ponce,et al.  Accurate, Dense, and Robust Multiview Stereopsis , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[20]  Richard Szeliski,et al.  Towards Internet-scale multi-view stereo , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[21]  Radim Sara,et al.  Refinement of Surface Mesh for Accurate Multi-View Reconstruction , 2010, Int. J. Virtual Real..