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Computer Vision Technologies and Historical Archaeology's Ceramic Typologies

Author(s): Patrice L Jeppson ; Kamelia Aryafar ; Ali Shokoufandeh

Year: 2013

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Computer vision technologies will someday reconstruct our ceramics for us. This paper considers the implications of one new development toward that end – a computer-employed 'appearance analysis' that automates the classification of ceramic fragments. This technology, which forms a first step in virtual ceramic reconstructions, parallels the typological ordering archaeologists traditionally employ when mending vessels and pursuing cultural understandings. On a prosaic level, the automated matching of surface (decorative) markings will drastically reduce the time and cost of lab work. More substantively, the ways that computer algorithms process and analyze ceramic decoration differs from the typological categorizations used by the archaeologist. As such, the computer-aided learning schema encourages self-reflection about "the little categories of [typological] thought" that archaeologists commonly use with ceramics. This, in turn, helps expose hidden socio-cultural practices both within the field of historical archaeology and in the past it studies.

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Computer Vision Technologies and Historical Archaeology's Ceramic Typologies. Patrice L Jeppson, Kamelia Aryafar, Ali Shokoufandeh. Presented at Society for Historical Archaeology, Leicester, England, U.K. 2013 ( tDAR id: 428504)


Spatial Coverage

min long: -129.199; min lat: 24.495 ; max long: -66.973; max lat: 49.359 ;

Record Identifiers

PaperId(s): 598

Arizona State University The Andrew W. Mellon Foundation National Science Foundation National Endowment for the Humanities Society for American Archaeology Archaeological Institute of America