Fully Automatic, Omnidirectional Acquisition of Geometry and Appearance in the Context of Cultural Heritage Preservation

Effective documentation and display of ancient objects is an essential task in the field of cultural heritage conservation. Digitization plays an important role in the process of creating, preserving, and accessing objects in digital space. Up to the present day, industrial scanners are used for this task, which focus mainly on the detailed reconstruction of the object’s geometry only. However, particularly important for a faithful digital presentation of the object is the appearance information—that is, a description of the used materials and how they interact with incident light. Using the world’s first full-spherical scanner, we propose a user-friendly reconstruction process that is specifically tailored to the needs of digitizing and representing cultural heritage artifacts. More precisely, our hardware specifically addresses the problem that invaluable or fragile artifacts may not be turned over during acquisition. Nevertheless, we can digitize the object completely, including its bottom. Further, by integrating appearance information into our digitization, we achieve a far more faithful digital replica with a quality comparable to a real picture of the object. But in contrast to a static picture, our representation allows one to interactively change the viewing and lighting directions freely. In addition, the results are very memory efficient, consuming only several megabytes per scanned object. In cooperation with museums and a private collector, we digitized several cultural heritage artifacts to demonstrate the feasibility of the proposed process.

[1]  Todd E. Zickler,et al.  A coaxial optical scanner for synchronous acquisition of 3D geometry and surface reflectance , 2010, ACM Trans. Graph..

[2]  Roberto Scopigno,et al.  A Statistical Method for SVBRDF Approximation from Video Sequences in General Lighting Conditions , 2012, Comput. Graph. Forum.

[3]  Dung A. Nguyen,et al.  Some practical considerations in fringe projection profilometry , 2010 .

[4]  Andrea Fusiello,et al.  Practical Autocalibration , 2010, ECCV.

[5]  Charles A. Poynton,et al.  Gamma and Its Disguises : The Nonlinear Mappings of Intensity in Perception, CRTs, Film, and Video , 1993 .

[6]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[7]  Wan-Chun Ma,et al.  The Digital Emily Project: Achieving a Photorealistic Digital Actor , 2010, IEEE Computer Graphics and Applications.

[8]  Visesh Chari,et al.  A theory of multi-layer flat refractive geometry , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[9]  M. Z. Haq,et al.  APPLIED MEASUREMENT SYSTEMS , 2016 .

[10]  Didier Stricker,et al.  A full-spherical device for simultaneous geometry and reflectance acquisition , 2013, 2013 IEEE Workshop on Applications of Computer Vision (WACV).

[11]  Reinhard Klein Erfassung und Präsentation digitaler Replica von Artefakten des kulturellen Erbes Acquisition and Presentation of Virtual Surrogates for Cultural Heritage Artefacts , 2012 .

[12]  Michael H. Brill,et al.  Color appearance models , 1998 .

[13]  J. Koenderink,et al.  Phenomenological description of bidirectional surface reflection , 1998 .

[14]  Reinhard Klein,et al.  Rapid Synchronous Acquisition of Geometry and Appearance of Cultural Heritage Artefacts , 2005, VAST.

[15]  V. Lepetit,et al.  EPnP: An Accurate O(n) Solution to the PnP Problem , 2009, International Journal of Computer Vision.

[16]  Hans-Peter Seidel,et al.  Image-based reconstruction of spatial appearance and geometric detail , 2003, TOGS.

[17]  S. Bougnoux,et al.  From projective to Euclidean space under any practical situation, a criticism of self-calibration , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[18]  M. Brooks,et al.  Recovering unknown focal lengths in self-calibration: an essentially linear algorithm and degenerate configurations , 1996 .

[19]  Paolo Cignoni,et al.  Surface light field from video acquired in uncontrolled settings , 2013, 2013 Digital Heritage International Congress (DigitalHeritage).

[20]  Jitendra Malik,et al.  Recovering high dynamic range radiance maps from photographs , 1997, SIGGRAPH '08.

[21]  Didier Stricker,et al.  Faithful, compact and complete digitization of cultural heritage using a full-spherical scanner , 2013, 2013 Digital Heritage International Congress (DigitalHeritage).

[22]  Mark D. Fairchild,et al.  Color Appearance Models: Fairchild/Color Appearance Models , 2013 .

[23]  Christopher Schwartz,et al.  Integrated High-Quality Acquisition of Geometry and Appearance for Cultural Heritage , 2011, VAST.

[24]  G LoweDavid,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004 .

[25]  Didier Stricker,et al.  High Quality and Memory Efficient Representation for Image Based 3D Reconstructions , 2012, 2012 International Conference on Digital Image Computing Techniques and Applications (DICTA).

[26]  Richard Szeliski,et al.  The lumigraph , 1996, SIGGRAPH.

[27]  Didier Stricker,et al.  Robust Outlier Removal from Point Clouds Acquired with Structured Light , 2012, Eurographics.

[28]  Mahdi Nezamabadi,et al.  Color Appearance Models , 2014, J. Electronic Imaging.

[29]  F. E. Nicodemus Directional Reflectance and Emissivity of an Opaque Surface , 1965 .

[30]  Bongtae Han,et al.  Advanced iterative algorithm for phase extraction of randomly phase-shifted interferograms. , 2004, Optics letters.

[31]  Bernhard P. Wrobel,et al.  Multiple View Geometry in Computer Vision , 2001 .

[32]  Manolis I. A. Lourakis,et al.  SBA: A software package for generic sparse bundle adjustment , 2009, TOMS.

[33]  Nicola D'Apuzzo,et al.  Overview of 3D surface digitization technologies in Europe , 2006, Electronic Imaging.

[34]  Gregory J. Ward,et al.  Measuring and modeling anisotropic reflection , 1992, SIGGRAPH.

[35]  Kenneth Levenberg A METHOD FOR THE SOLUTION OF CERTAIN NON – LINEAR PROBLEMS IN LEAST SQUARES , 1944 .

[36]  Andrew Zisserman,et al.  Multiple View Geometry in Computer Vision (2nd ed) , 2003 .

[37]  Katsushi Ikeuchi,et al.  Appearance Based Object Modeling using Texture Database: Acquisition Compression and Rendering , 2002, Rendering Techniques.