This paper presents the results of the SHREC'18 track: Retrieval of gray patterns depicted on 3D models. The task proposed in the contest challenges the possibility of retrieving surfaces with the same texture pattern of a given query model. This task, which can be seen as a simplified version of many real world applications, requires a characterization of the surfaces based on local features, rather then considering the surface size and/or bending. All runs submitted to this track are based on feature vectors. The retrieval performances of the runs submitted for evaluation reveal that texture pattern retrieval is a challenging issue. Indeed, a good balance between the size of the pattern and the dimension of the region around a vertex used to locally analyze the color evolution is crucial for pattern description.

SHREC'18 track: Retrieval of gray patterns depicted on 3D models

E Moscoso Thompson;S Biasotti
2018

Abstract

This paper presents the results of the SHREC'18 track: Retrieval of gray patterns depicted on 3D models. The task proposed in the contest challenges the possibility of retrieving surfaces with the same texture pattern of a given query model. This task, which can be seen as a simplified version of many real world applications, requires a characterization of the surfaces based on local features, rather then considering the surface size and/or bending. All runs submitted to this track are based on feature vectors. The retrieval performances of the runs submitted for evaluation reveal that texture pattern retrieval is a challenging issue. Indeed, a good balance between the size of the pattern and the dimension of the region around a vertex used to locally analyze the color evolution is crucial for pattern description.
2018
Istituto di Matematica Applicata e Tecnologie Informatiche - IMATI -
978-3-03868-053-6
Computer Graphics: Picture/Image Generation--Line and curve generation
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Descrizione: SHREC'18 track: Retrieval of gray patterns depicted on 3D models
Tipologia: Versione Editoriale (PDF)
Dimensione 2.2 MB
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2.2 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/376208
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