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Visual Analysis in Archaeology. An Artificial Intelligence Approach

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Morphometrics for Nonmorphometricians

Part of the book series: Lecture Notes in Earth Sciences ((LNEARTH,volume 124))

Abstract

Archaeology is a quintessentially “visual” discipline, because visual perception makes us aware of fundamental properties of objects and allows us to discover how objects were produced and used in the past. The approach I adopt here is to follow current computational theories of visual perception to ameliorate to way archaeology can deal with the analysis and explanation of the most usual visual marks: shape and texture. In any case, I am not interested in the mere mechanical procedure of extracting shape information among visual input, but in explaining why archaeological evidences have the shape they have.

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Acknowledgments

Special thanks to Marcelo Cardillo for comments on a previous version of this paper. Erik Otarola-Castillo and R. Sant-Amant sent me details of their interesting research. Xavier Clop, Mercedes Farjas and F.J. Melero have also contributed to my understanding of what should be a comprehensive visual analysis in archaeology. Thanks also to my students at the Dept. of prehistory (Universitat Autònoma de Barcelona, Spain) who are beginning to explore the many possibilities of shape analysis in archaeology. Parts of this research have been funded by the Spanish Ministry of Science and Innovation, The Generalitat de Catalunya and the Universitat Autònoma de Barcelona.

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  1. Departament de Prehistòria, Facultat de Lletres, Universitat Autònoma de Barcelona, Campus Bellaterra, 08193, Barcelona, Cerdanyola, España

    Juan A. Barceló

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  1. Fac. Science, Dept. Geology, Minia University, Minia, 61519, Egypt

    Ashraf M.T. Elewa

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Barceló, J.A. (2010). Visual Analysis in Archaeology. An Artificial Intelligence Approach. In: Elewa, A. (eds) Morphometrics for Nonmorphometricians. Lecture Notes in Earth Sciences, vol 124. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-95853-6_5

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