A 3D reconstruction pipeline for digital preservation

We present a new 3D reconstruction pipeline for digital preservation of natural and cultural assets. This application requires high quality results, making time and space constraints less important than the achievable precision. Besides the high quality models generated, our work allows an overview of the entire reconstruction process, from range image acquisition to texture generation. Several contributions are shown, which improve the overall quality of the obtained 3D models. We also identify and discuss many practical problems found during the pipeline implementation. Our objective is to help future works of other researchers facing the challenge of creating accurate 3D models of real objects.

[1]  M. Pauline Baker,et al.  Computer Graphics 2nd Ed , 2008 .

[2]  Thomas Lewiner,et al.  Efficient Implementation of Marching Cubes' Cases with Topological Guarantees , 2003, J. Graphics, GPU, & Game Tools.

[3]  Andrew Zisserman,et al.  MLESAC: A New Robust Estimator with Application to Estimating Image Geometry , 2000, Comput. Vis. Image Underst..

[4]  Avinash C. Kak,et al.  3D Modeling of Optically Challenging Objects , 2008, IEEE Transactions on Visualization and Computer Graphics.

[5]  Katsushi Ikeuchi,et al.  Hole Filling of a 3D Model by Flipping Signs of a Signed Distance Field in Adaptive Resolution , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  Atsushi Nakazawa,et al.  The Great Buddha Project: Digitally Archiving, Restoring, and Analyzing Cultural Heritage Objects , 2007, International Journal of Computer Vision.

[7]  Steve Marschner,et al.  Filling holes in complex surfaces using volumetric diffusion , 2002, Proceedings. First International Symposium on 3D Data Processing Visualization and Transmission.

[8]  Yutaka Takase,et al.  The Great Buddha Project: Modelling Cultural Heritage through Observation , 2001 .

[9]  Linda G. Shapiro,et al.  View-base Rendering: Visualizing Real Objects from Scanned Range and Color Data , 1997, Rendering Techniques.

[10]  Bruno Lévy,et al.  Mesh parameterization: theory and practice , 2007, SIGGRAPH Courses.

[11]  Richard K. Beatson,et al.  Reconstruction and representation of 3D objects with radial basis functions , 2001, SIGGRAPH.

[12]  Katsushi Ikeuchi,et al.  Adaptively merging large-scale range data with reflectance properties , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[13]  Diego F. Nehab,et al.  Efficiently combining positions and normals for precise 3D geometry , 2005, SIGGRAPH 2005.

[14]  David Fofi,et al.  A review of recent range image registration methods with accuracy evaluation , 2007, Image Vis. Comput..

[15]  Marc Levoy,et al.  A volumetric method for building complex models from range images , 1996, SIGGRAPH.

[16]  Holly E. Rushmeier,et al.  The 3D Model Acquisition Pipeline , 2002, Comput. Graph. Forum.

[17]  Marc Levoy,et al.  Efficient variants of the ICP algorithm , 2001, Proceedings Third International Conference on 3-D Digital Imaging and Modeling.

[18]  Hugues Hoppe,et al.  New quadric metric for simplifying meshes with appearance attributes , 1999, Proceedings Visualization '99 (Cat. No.99CB37067).

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

[20]  N. Mitra,et al.  4-points congruent sets for robust pairwise surface registration , 2008, SIGGRAPH 2008.

[21]  Holly E. Rushmeier,et al.  High-Quality Texture Reconstruction from Multiple Scans , 2001, IEEE Trans. Vis. Comput. Graph..

[22]  William E. Lorensen,et al.  Marching cubes: A high resolution 3D surface construction algorithm , 1987, SIGGRAPH.

[23]  Katsushi Ikeuchi,et al.  Consensus surfaces for modeling 3D objects from multiple range images , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[24]  Xiaolin Wu.  A linear-Time Simple Bounding Volume Algorithm , 1992, Graphics Gems III.

[25]  Marc Levoy,et al.  The digital Michelangelo project: 3D scanning of large statues , 2000, SIGGRAPH.

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

[27]  Gabriel Taubin,et al.  Building a Digital Model of Michelangelo's Florentine Pietà , 2002, IEEE Computer Graphics and Applications.

[28]  Hugues Hoppe,et al.  Progressive meshes , 1996, SIGGRAPH.

[29]  Kari Pulli,et al.  Multiview registration for large data sets , 1999, Second International Conference on 3-D Digital Imaging and Modeling (Cat. No.PR00062).

[30]  Hans-Peter Seidel,et al.  Multi-level partition of unity implicits , 2005, SIGGRAPH Courses.

[31]  George Pavlidis,et al.  Methods for 3D digitization of Cultural Heritage , 2007 .

[32]  Alla Sheffer,et al.  Mesh parameterization: theory and practice Video files associated with this course are available from the citation page , 2007, SIGGRAPH Courses.