Presentation given at #sotonboat @sotonarch 20 May 2013

1. Digital Archaeology:
Imaging & Visualisation @sotonarch
Graeme Earl, Boat Recording #sotonboats , 20 May 2013
http://acrg.soton.ac.uk

3. Archaeological Computing
Research Group
Tweeting as:
@ArchCRG

4. Some ACRG PhDs
• Complexity science and hominid dispersal – Complex
Systems Simulation
• Multispectral, microscopic imaging– ECS
• Structural and flood simulation of Winchester Cathedral –
Engineering
• Light and the past – perception, functional behaviour,
simulation – Chemistry, Geography, Art & Physics
• The sound of the past – ISVR

5. Archaeology and Visual Data
• Imaging
• Computer Vision
• Visualisation
• Capture & Delivery
Image from BBC/ Discovery – Rome What Lies beneath
http://www.portusproject.org/blog/2012/12/reconstructing-portus/

6. Imaging
• Micro-CT
• e.g. Roman cremations
See http://www.guardian.co.uk/science/2012/jul/09/x-
rays-reveal-secrets-roman-coins and
http://www.bbc.co.uk/news/technology-21235980

7. Imaging
• Photographic
• e.g. photometric stereo
See http://acrg.soton.ac.uk/tag/rti/

8. Imaged materials
• amphora stamps
• brick stamps
• bronze bust
• carved architectural stone
• ceramics
• clovis points
• coins
• cuneiform tablets
• excavated context
• graffiti (modern, second world war, medieval)
• gravestones
• handaxes
• inscriptions
• jade disc
• Linear A and Linear B tablets
• medieval icons
• medieval metalwork
• mosaics
• paintings
• pigment
• plaster (surfaces and decoration)
• porcelain
• seals
• squeezes
• stone sculpture
• tituli picti
• tool and cut marks in wood, bone and stone
• wall paintings
• roman wood, lead and selenite tablets
• wood (waterlogged, PEG treated,
moulds, casts)

9. Imaging
• Photographic e.g. photometric stereo
Captures and processing by Hembo Pagi and Eleni Kotoula/

10. Lime wood, gold and encaustic (hot wax) mummy portrait (160-170AD) from Rubaiyat, Egypt (British Museum) – captured
as part of AHRC funded RTISAD project http://acrg.soton.ac.uk/tag/rtisad/

11. 1 degree minimum angle difference between normals (thicker = steeper)

12. Normal quality determined by input data and the fitting algorithm
Most applications are interested in qualitative assessment; relative metric calculations are internally robust

13. 1 degree minimum angle difference between normals
(thicker = steeper)
Rendered view with raking light

14. Normal comparisons/ search
• Per-pixel comparisons (Dellapiane et al 2006)
• On-going work by Lindsay MacDonald (UCL)
and Mark Drew (Simon Fraser University)
• Opportunities posed by flatbed scanners: e.g.
Ruggero Pintus et al 2009 and Brown et al
2008
• Our own work used pseudo surface matching;
most recently a solely normal-based approach
using RAW data and CGI libraries
• Normal-based image segmentation using CGI
toolsets (but note: benefits of CARE system)
Earl, G.P., Martinez, K. and Malzbender, T. 2010. Archaeological Applications of
Polynomial Texture Mapping: Analysis, Conservation and Representation. Journal
Archaeological Science 37

15. CARE
• Collaborative Algorithmic Rendering tool
Illustration of Complex Real-World Objects using Images
with Normals.
Corey Toler-Franklin, Adam Finkelstein, and Szymon
Rusinkiewicz.
International Symposium on Non-Photorealistic Animation
and Rendering (NPAR), San Diego, CA, 2007.

16. Computer Vision
• Photogrammetry
• (Gigapixel)
• (Examples from Daniel
Joyce and James Miles)

17. Visualisation
• Networks and Rendering
• e.g. Iridis3 supercomputer
• e.g. Çatalhöyük
Photographs from Catalhoyuk Project
and CGI by Grant Cox

18. CGI visualisations by Grant Cox, on
data from Staffordshire Hoard and
Catalhoyuk Project

19. Capture & Delivery
• Scanning
• e.g. recording Portus
Photographs and scan data by PA, Gareth Beale and James
Miles from Portus

20. Capture & Delivery
• Mixed reality
• e.g. mobile computing for site interpretation and recording

21. 3d Semantics
• On-going work to annotate 3d datasets
• 3D-COFORM project
• University of Queensland:
http://itee.uq.edu.au/~eresearch/projects/3dsa/index.php
#overview
NICCOLUCCI F and A. D'ANDREA, "An Ontology for 3D Cultural Objects," in VAST 2006: 7th International
Symposium on Virtual Reality, Archaeology and Intelligent Cultural Heritage, 2006, pp. 203-210.
KOLLER, D. B. FRISCHER and G. HUMPHREYS. 2009 Research Challenges for Digital Archives of 3D
Cultural Heritage Models. ACM Journal on Computing and Cultural Heritage, Vol. 2, No. 3, Article 7.

22. Image Peter Bennett – RCUK PATINA Project

23. Scan data produced by Microsoft Kinect – James Miles and Jarrod Knibbe – RCUK
PATINA Project

24. Scan data produced by Microsoft Kinect – Jarrod Knibbe – RCUK PATINA Project

25. Citizen science & imaging

26. Repositories
• Ancient document artefacts: Oxford archive; Cuneiform Digital Library
Initiative
• Archaeological data:
• ADS repository (primary archive)
• JISC IDMB pilot repository
• JISC DepositMO toolset
• JISC DataPool
• JISC DepositMOre
• Access to resources via:
• RTIviewer (local and streamed on-line)
• (SpiderGL)
• New AHRC RTI project @AHRCRTI
Archiving

27. On-going research focus
• Real time and predictive rendering
• Data integration e.g. scan, vector, photogrammetry
• Sensor and capture technologies
• Data visualisation
• Web technologies e.g. 3d linked data
• Educational frameworks e.g. 3d technology MOOCs (see for
example developments of our Portus mini MOOC)

28. Thanks
@GraemeEarl
Graeme Earl, Boat Recording, 20 May 2013 http://acrg.soton.ac.uk