Functional analysis from visual and non-visual data : An artificial intelligence approach

Part of : Mediterranean archaeology & archaeometry : international journal ; Vol.12, No.2, 2012, pages 273-321

Issue:
Pages:
273-321
Section Title:
Articles
Author:
Abstract:
Why archaeological artefacts are the way they are? In this paper we try to solve such a question by investigating the relationship between form and function. We propose new ways of studying the way behaviour in the past can be asserted on the examination of archaeological observables in the present. In any case, we take into account that there are also non-visual features characterizing ancient objects and materials (i.e., compositional information based on mass spectrometry data, chronological information based on radioactive decay measurements, etc.). Information that should make us aware of many functional properties of objects is multidimensional in nature: size, which makes reference to height, length, depth, weight and mass; shape and form, which make reference to the geometry of contours and volumes; texture, which refers to the microtopography (roughness, waviness, and lay) and visual appearance (colour variations, brightness, reflectivity and transparency) of surfaces; and finally material, meaning the combining of distinct compositional elements and properties to form a whole. With the exception of material data, the other relevant aspects for functional reasoning have been traditionally described in rather ambiguous terms, without taking into account the advantages of quantitative measurements of shape/form, and texture. Reasoning about the functionality of archaeological objects recovered at the archaeological site requires a cross-disciplinary investigation, which may also range from recognition techniques used in computer vision and robotics to reasoning, representation, and learning methods in artificial intelligence. The approach we adopt here is to follow current computational theories of object perception to ameliorate the way archaeology can deal with the explanation of human behaviour in the past (function) from the analysis of visual and non-visual data, taking into account that visual appearances and even compositional characteristics only constrain the way an object may be used, but never fully determine it.
Subject:
Subject (LC):
Keywords:
Function, Shape, Form, Texture, Material, Artificial Intelligence
Notes:
Corresponding author: juanantonio.barcelo@uab.es, The authors thank the following people and institutions mostly for their continuous work, support, and enthusiasm towards this multidisciplinary research: The Institucio Mila i Fontanals, Consejo Superior de Investigacion Cientifica (IMFCSIC), for having provided us the 3D scanner, without which we would not have been able to capture the 3D digital models of the archaeological wooden artefacts of La Draga (Banyoles, Catalonya). The codirectors of the 2011 and 2012 excavation campaigns of La Draga, Raquel Pique (UAB), Antoni Palomo (Arqueolitic/ UAB), Xavier Terradas (IMF-CSIC), Maria Sana (UAB); and the Museum of Banyoles, in the name of its director Josep Tarrus, for making available the artefacts to be 306 J.A. BArCELO et al scanned. Antonio Nadal Gisbert, from the Departamento de Ingenieria Mecanica y de Materiales, Campus de Alcoy, Polytechnic University of Valencia (UPV), for providing us the means and the scientific knowledge to adequately test the physical and mechanical properties of modern wood samples. The Oficina Tecnica de Parcs Naturals de la Diputacio de Barcelona; the Parcs i Jardins de Barcelona, from Barcelona City Council; The Natural Park of the Volcanic Area of La Garrotxa, Catalonia; and the Centre de Cooperation Internationale en Recherche Agronomique pour le Developpement (CIRAD), in Montpellier, for managing to arrange us modern wood logs. This research is part of the project PADICAT (Patrimoni Digital Arqueologic de Catalunya), funded by the Obra Social la Caixa and the Asociacio d'Universitats Catalanes (Programa RecerCaixa, RECER2010-05), as well as of the project “Experimenting and developing advanced computational intelligence techniques for simulating social dynamics and historical evolution", funded by The Spanish Ministry of Science and Innovation in the period 2010-2012 (Grant HAR2009-12258). This research also benefits from Vera Moitinho’s Ph.D. grant from the Fundacao para a Ciencia e Tecnologia (FCT), Portugal, cofunded by the European Social Fund. Thanks to two anonymous reviewers and to Ioannis Liritzis for a welcomed criticism that helped us to express our ideas in a more understandable way. In any case, the authors are the only responsable for expressed ideas and for any mistake that may remain in the text.
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