Computer vision and machine learning for archaeology

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Computer vision and machine learning for
archaeology

• The potential of machine learning and image
  analysis techniques for the domain of archaeology
• Drs. L. van der Maaten, Drs. P.J. Boon, Dr. A.G.
  Lange, Dr. H. Paijmans, Prof.dr. E.O. Postma
• Paul Boonp.boon_at_cs.unimaas.nl
• http//www.referentiecollectie.nl/rich
• Institute for Knowledge and Agent Technology
• Maastricht University

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Outline

• Introduction
• Why How
• Computer vision and machine learning
• Examples
• Historical glass, on-line reference collection
• Modern coins
• Conclusion
• Future work

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Why How

• Need for on-line reference collections
• Making a collection digital is not enough
• Create tools for identifying artifacts
• Vision and machine learning for finding alike
  objects
• Web technology for presentation and navigation

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Computer vision and machine learning
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Computer vision and machine learning

1. Object detection
2. Feature extraction
3. Classification

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Computer vision and machine learning
Not a replacement, but a tool!
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Example

• Historical glass
• Content based image retrieval
• Outer shape contours

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Object detection
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Shape context
Translation, scale and rotation invariant





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Histogram construction
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Classification
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Example

• Coins
• Automatic classification system, using texture
  information
• Modern coins, but in future early-medieval coins

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Original
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Object detection
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Features
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Conclusion

• You can successfully integrate computer vision
  and machine learning with an online collection

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Future work

• Improve usefulness
• Object detection
• Evaluate technology
• Other types of material
• Using outer shape and texture
• Partial shapes, from sherds?
• Evaluate typologies or device new ones?

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Shape map
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Acknowledgements

• We thank the Dutch Royal Coin Cabinet for
  providing the medieval coin datasetArent Pol
  specialist on early-medieval coins