research-article

A system for high-volume acquisition and matching of fresco fragments: reassembling Theran wall paintings

Authors:

Benedict J. Brown,

Corey Toler-Franklin,

Andreas Vlachopoulos,

Christos Doumas,

Szymon Rusinkiewicz,

Tim WeyrichAuthors Info & Claims

ACM Transactions on Graphics (TOG), Volume 27, Issue 3

Pages 1 - 9

https://doi.org/10.1145/1360612.1360683

Published: 01 August 2008 Publication History

Abstract

Although mature technologies exist for acquiring images, geometry, and normals of small objects, they remain cumbersome and time-consuming for non-experts to employ on a large scale. In an archaeological setting, a practical acquisition system for routine use on every artifact and fragment would open new possibilities for archiving, analysis, and dissemination. We present an inexpensive system for acquiring all three types of information, and associated metadata, for small objects such as fragments of wall paintings. The acquisition system requires minimal supervision, so that a single, non-expert user can scan at least 10 fragments per hour. To achieve this performance, we introduce new algorithms to robustly and automatically align range scans, register 2-D scans to 3-D geometry, and compute normals from 2-D scans. As an illustrative application, we present a novel 3-D matching algorithm that efficiently searches for matching fragments using the scanned geometry.

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References

[1]

Arun, K. S., Huang, T. S., and Blostein, S. D. 1987. Least-Squares Fitting of Two 3-D Point Sets. IEEE Trans. PAMI, Vol. 9, No. 5, 698--700.

Digital Library

[2]

Bernardini, F., Rushmeier, H., Martin, I. M., Mittleman, J., and Taubin, G. 2002. Building a Digital Model of Michelangelo's Florentine Pietà. IEEE Computer Graphics and Applications, Vol. 22, No. 1, 59--67.

Digital Library

[3]

Besl, P. J., and McKay, N. D. 1992. A Method for Registration of 3-D Shapes. IEEE Trans. PAMI, Vol. 14, No. 2, 239--256.

Digital Library

[4]

Bracci, S., Falletti, F., Matteini, M., and Scopigno, R., Eds. 2004. Exploring David: Diagnostic Tests and State of Conservation. Giunti Press, Florence, Italy.

[5]

Brown, B. J. 2008. Registration and Matching of Large Geometric Datasets for Cultural Heritage Applications. Ph.D. thesis, Princeton Univ.

Digital Library

[6]

Chen, Y., and Medioni, G. 1992. Object Modeling by Registration of Multiple Range Images. Image and Vision Computing, Vol. 10, No. 3, 145--155.

Digital Library

[7]

Doumas, C. 1992. The Wall-Paintings of Thera. Thera Foundation - P. M. Nomikos, Athens.

[8]

Fornasier, M., and Toniolo, D. 2005. Fast, Robust and Efficient 2D Pattern Recognition for Re-Assembling Fragmented Images. Pattern Recognition, Vol. 38, No. 11, 2074--2087.

Digital Library

[9]

Gardner, A., Tchou, C., Hawkins, T., and Debevec, P. 2003. Linear Light Source Reflectometry. ACM Trans. Graphics (Proc. SIGGRAPH), Vol. 22, No. 3, 749--758.

Digital Library

[10]

Gelfand, N., Ikemoto, L., Rusinkiewicz, S., and Levoy, M. 2003. Geometrically Stable Sampling for the ICP Algorithm. In Proc. 3DIM, 260--267.

[11]

Huang, Q.-X., Flöry, S., Gelfand, N., Hofer, M., and Pottmann, H. 2006. Reassembling Fractured Objects by Geometric Matching. ACM Trans. Graphics (Proc. SIGGRAPH), Vol. 25, No. 3, 569--578.

Digital Library

[12]

Johnson, A., and Hebert, M. 1997. Surface Registration by Matching Oriented Points. In Proc. 3DIM, 121--128.

Digital Library

[13]

Karasik, A., and Smilansky, U. 2008. 3D Scanning Technology as a Standard Archaeological Tool for Pottery Analysis: Practice and Theory. Journal of Archaeological Science, Vol. 35, 1148--1168.

[14]

Koller, D., Trimble, J., Najbjerg, T., Gelfand, N., and Levoy, M. 2006. Fragments of the City: Stanford's Digital Forma Urbis Romae Project. In Proc. Third Williams Symposium on Classical Architecture, Journal of Roman Archaeology, vol. Suppl. 61, 237--252.

[15]

Kong, W., and Kimia, B. 2001. On Solving 2D and 3D Puzzles under Curve Matching. In Proc. CVPR, vol. 2, 583--590.

[16]

Leitão, H. C. G., and Stolfi, J. 2002. A Multiscale Method for the Reassembly of Two-Dimensional Fragmented Objects. IEEE Trans. PAMI, Vol. 24, No. 9, 1239--1251.

Digital Library

[17]

Lensch, H. P., Heidrich, W., and Seidel, H. 2000. Automated Texture Registration and Stitching for Real World Models. In Proc. Pacific Graphics, 317--326.

Digital Library

[18]

Levoy, M., Pulli, K., Curless, B., Rusinkiewicz, S., Koller, D., Pereira, L., Ginzton, M., Anderson, S., Davis, J., Ginsberg, J., Shade, J., and Fulk, D. 2000. The Digital Michelangelo Project: 3-D Scanning of Large Statues. In Proc. SIGGRAPH, 131--144.

Digital Library

[19]

Lowe, D. G. 2004. Distinctive Image Features from Scale-Invariant Keypoints. IJCV, Vol. 60, No. 2, 91--110.

Digital Library

[20]

Nehab, D., Rusinkiewicz, S., Davis, J., and Ramamoorthi, R. 2005. Efficiently Combining Positions and Normals for Precise 3D Geometry. ACM Trans. Graphics (Proc. SIGGRAPH), Vol. 24, No. 3, 536--543.

Digital Library

[21]

Papaodysseus, C., Panagopoulos, T., Exarhos, M., Triantafillou, C., Fragoulis, D., and Doumas, C. 2002. Contour-Shape Based Reconstruction of Fragmented, 1600 BC Wallpaintings. IEEE Trans. on Signal Processing, Vol. 50, No. 6, 1277--1288.

Digital Library

[22]

Rusinkiewicz, S., and Levoy, M. 2001. Efficient Variants of the ICP Algorithm. In Proc. 3DIM, 145--152.

[23]

Saǧiroǧlu, M. Ş., and Erçil, A. 2006. A Texture Based Matching Approach for Automated Assembly of Puzzles. In Proc. ICPR, vol. 3, 1036--1041.

Digital Library

[24]

Toler-Franklin, C., Finkelstein, A., and Rusinkiewicz, S. 2007. Illustration of Complex Real-World Objects using Images with Normals. In Proc. NPAR, 111--119.

Digital Library

[25]

Vlachopoulos, A. 2008. The Wall Paintings from the Xeste 3 building at Akrotiri. Towards an Interpretation of the Iconographic Programme. In Horizons: A colloquium on the prehistory of the Cyclades, Cambridge, N. Brodie, J. Doole, G. Gavalas, and C. Renfrew, Eds., 451--465.

[26]

Wasserman, J., Camiz, F. T., Verdon, T., and Rockwell, P. 2002. Michelangelo's Florence Pietà. Princeton Univ. Press.

[27]

Willis, A. 2004. Stochastic 3D Geometric Models for Classification, Deformation, and Estimation. Ph. D. thesis, Brown Univ.

Digital Library

[28]

Woodham, R. J. 1980. Photometric Method for Determining Surface Orientation from Multiple Images. Optical Engineering, Vol. 19, No. 1, 139--144.

Cited By

Altansukh AYou MAltantsetseg EKhorloo OChiba FKonno K(2024)A New Matching Algorithm for Stone Tool Reassembly Based on Contour Points of Flake SurfaceThe Journal of the Society for Art and Science10.3756/artsci.23.4_123:2(4_1-4_17)Online publication date: 26-Jun-2024
https://doi.org/10.3756/artsci.23.4_1
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https://doi.org/10.3724/2097-3063.20240016
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Index Terms

A system for high-volume acquisition and matching of fresco fragments: reassembling Theran wall paintings
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision representations
        Shape representations
      2. Image and video acquisition
  2. Machine learning
    1. Learning paradigms
      1. Unsupervised learning
        Cluster analysis
2. Theory of computation
  1. Design and analysis of algorithms
    1. Data structures design and analysis
      1. Pattern matching

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Published In

cover image ACM Transactions on Graphics

ACM Transactions on Graphics Volume 27, Issue 3

August 2008

844 pages

ISSN:0730-0301

EISSN:1557-7368

DOI:10.1145/1360612

Issue’s Table of Contents

Copyright © 2008 ACM.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 August 2008

Published in TOG Volume 27, Issue 3

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Cited By

Altansukh AYou MAltantsetseg EKhorloo OChiba FKonno K(2024)A New Matching Algorithm for Stone Tool Reassembly Based on Contour Points of Flake SurfaceThe Journal of the Society for Art and Science10.3756/artsci.23.4_123:2(4_1-4_17)Online publication date: 26-Jun-2024
https://doi.org/10.3756/artsci.23.4_1
YANG XLI F(2024)Artificial intelligence-assisted restoration and visualization of knapped stone toolsPrehistoric Archaeology10.3724/2097-3063.202400161:2(207-223)Online publication date: 23-Jul-2024
https://doi.org/10.3724/2097-3063.20240016
Zheng YLi XWeng Y(2024)Reunion helper: an edge matcher for sibling fragment identification of the Dunhuang manuscriptHeritage Science10.1186/s40494-024-01150-312:1Online publication date: 13-Feb-2024
https://doi.org/10.1186/s40494-024-01150-3
Xu QChen HHua JZhan XYang YMu T(2024)FragmentDiff: A Diffusion Model for Fractured Object AssemblySIGGRAPH Asia 2024 Conference Papers10.1145/3680528.3687673(1-12)Online publication date: 3-Dec-2024
https://doi.org/10.1145/3680528.3687673
Yang MSvirsky YCheng ZSharf A(2024)Self-Supervised Fragment Alignment With GapsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2023.333085930:9(6235-6246)Online publication date: 1-Sep-2024
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Scarpellini GFiorini SGiuliari FMorerio PBue A(2024)DiffAssemble: A Unified Graph-Diffusion Model for 2D and 3D Reassembly2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR52733.2024.02654(28098-28108)Online publication date: 16-Jun-2024
https://doi.org/10.1109/CVPR52733.2024.02654
Harris ACremaschi ALim TDe Iorio MKwa C(2024)From past to future: digital methods towards artefact analysisDigital Scholarship in the Humanities10.1093/llc/fqae05739:4(1026-1042)Online publication date: 16-Oct-2024
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Khoroshiltseva MPalmieri LAslan SVascon SPelillo M(2024)Nash Meets Wertheimer: Using Good Continuation in Jigsaw PuzzlesComputer Vision – ACCV 202410.1007/978-981-96-0960-4_29(480-495)Online publication date: 8-Dec-2024
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Wang JZhang CWang PLi XCobb PTheobalt CWang W(2023)Batch-based Model Registration for Fast 3D Sherd Reconstruction2023 IEEE/CVF International Conference on Computer Vision (ICCV)10.1109/ICCV51070.2023.01335(14473-14483)Online publication date: 1-Oct-2023
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Deng ZJiang JChen ZZhang WYao QSong CSun YYang ZYan SHuang QBajaj C(2023)TAssemblyComputers and Graphics10.1016/j.cag.2023.05.003113:C(102-112)Online publication date: 1-Jun-2023
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