Publikation: Data-aware 3D partitioning for generic shape retrieval
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2013
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Computers & Graphics. 2013, 37(5), pp. 460-472. ISSN 0097-8493. Available under: doi: 10.1016/j.cag.2013.04.002
Zusammenfassung
In this paper, we present a new approach for generic 3D shape retrieval based on a mesh partitioning scheme. Our method combines a mesh global description and mesh partition descriptions to represent a 3D shape. The partitioning is useful because it helps us to extract additional information in a more local sense. Thus, part descriptions can mitigate the semantic gap imposed by global description methods. We propose to find spatial agglomerations of local features to generate mesh partitions. Hence, the definition of a distance function is stated as an optimization problem to find the best match between two shape representations. We show that mesh partitions are representative and therefore it helps to improve the effectiveness in retrieval tasks. We present exhaustive experimentation using the SHREC'09 Generic Shape Retrieval Benchmark.
Zusammenfassung in einer weiteren Sprache
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004 Informatik
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Mesh partitioning, optimization matching, shape retrieval
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SIPIRAN, Ivan, Benjamin BUSTOS, Tobias SCHRECK, 2013. Data-aware 3D partitioning for generic shape retrieval. In: Computers & Graphics. 2013, 37(5), pp. 460-472. ISSN 0097-8493. Available under: doi: 10.1016/j.cag.2013.04.002BibTex
@article{Sipiran2013Dataa-24360,
year={2013},
doi={10.1016/j.cag.2013.04.002},
title={Data-aware 3D partitioning for generic shape retrieval},
number={5},
volume={37},
issn={0097-8493},
journal={Computers & Graphics},
pages={460--472},
author={Sipiran, Ivan and Bustos, Benjamin and Schreck, Tobias}
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<dcterms:abstract xml:lang="eng">In this paper, we present a new approach for generic 3D shape retrieval based on a mesh partitioning scheme. Our method combines a mesh global description and mesh partition descriptions to represent a 3D shape. The partitioning is useful because it helps us to extract additional information in a more local sense. Thus, part descriptions can mitigate the semantic gap imposed by global description methods. We propose to find spatial agglomerations of local features to generate mesh partitions. Hence, the definition of a distance function is stated as an optimization problem to find the best match between two shape representations. We show that mesh partitions are representative and therefore it helps to improve the effectiveness in retrieval tasks. We present exhaustive experimentation using the SHREC'09 Generic Shape Retrieval Benchmark.</dcterms:abstract>
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