Thumbnail
Access Restriction
Subscribed

Author Buglio, David Lo ♦ Lardinois, Vanessa ♦ Luca, Livio De
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©2015
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Architectural representation ♦ Image processing ♦ Morphological analysis ♦ Semantic characterization
Abstract Over the past three decades, the introduction of digital technologies in the field of architectural documentation has profoundly changed tools and acquisition techniques. Most of the developments concern metrical and colorimetric characteristics of the objects studied. These developments, surrounding the practice of architectural survey, tend to respond primarily to the requirements of completeness. In this context, it seems necessary to assess the impact of these instruments on the cognitive value of architectural representation. With a strong technological presence, the study of the built heritage is facing a problem of “information overload.” Indeed, this strong technological presence fails to strengthen representation in its role as a vehicle of knowledge. Confronted with the intelligibility deficit, this article proposes an original approach for reading morphological features of an artifact by using a bottom-up approach: the meaning of elements (i.e., their semantic layouts) come from a statistical analysis of the major shape discontinuities of a collection of instances. The idea is to rely on data accumulation to render apparent high-level semantic structures from the comparative analysis of common low-level geometric features. The principles introduced are illustrated by the study of 31 columns of the cloister of the abbey of Saint-Michel-de-Cuxa. To summarize, the first objective is to understand how digital technologies can help us in the analysis of artistic and technical production of Romanesque columns. The second objective is to automatically identify the common semantic articulations of the entire collection to build a reference model for the future assessment of each artifact.
ISSN 15564673
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2015-02-01
Publisher Place New York
e-ISSN 15564711
Journal Journal on Computing and Cultural Heritage (JOCCH)
Volume Number 8
Issue Number 1
Page Count 18
Starting Page 1
Ending Page 18


Open content in new tab

   Open content in new tab
Source: ACM Digital Library