A 3D Shape Benchmark for Retrieval and Automatic Classification of Architectural Data
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Date
2009
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
When drafting new buildings, architects make intensive use of existing 3D models including building elements, furnishing, and environment elements. These models are either directly included into the draft or serve as a source for inspiration. To allow efficient reuse of existing 3D models, shape retrieval methods considering the specific requirements of architects must be developed. Unfortunately, common 3D shape benchmarks which are used to evaluate the performance of retrieval algorithms are not well suited for architectural data. First, they incorporate models which are not related to this domain, and second and even more important, the provided classification schemes usually do not match an architect's intuition regarding their notion of design and function. To overcome these drawbacks, we present a freely downloadable shape benchmark especially designed for architectural 3D models. It currently contains 2257 objects from various content providers, including companies specialized on 3D CAD applications. All models are classified according to a scheme developed in close cooperation with architects taking into account their specific requirements regarding design and function. Additionally, we show retrieval results for this benchmark using unsupervised and supervised shape retrieval methods and discuss the specific problems regarding retrieval of architectural 3D models.
Description
@inproceedings{:10.2312/3DOR/3DOR09/053-056,
booktitle = {Eurographics 2009 Workshop on 3D Object Retrieval},
editor = {Michela Spagnuolo and Ioannis Pratikakis and Remco Veltkamp and Theoharis Theoharis},
title = {{A 3D Shape Benchmark for Retrieval and Automatic Classification of Architectural Data}},
author = {Wessel, Raoul and Blümel, Ina and Klein, Reinhard},
year = {2009},
publisher = {The Eurographics Association},
ISSN = {1997-0463},
ISBN = {978-3-905674-16-3},
DOI = {/10.2312/3DOR/3DOR09/053-056}
}