author_facet Biasotti, S.
Cerri, A.
Giorgi, D.
Spagnuolo, M.
Biasotti, S.
Cerri, A.
Giorgi, D.
Spagnuolo, M.
author Biasotti, S.
Cerri, A.
Giorgi, D.
Spagnuolo, M.
spellingShingle Biasotti, S.
Cerri, A.
Giorgi, D.
Spagnuolo, M.
Computer Graphics Forum
PHOG: Photometric and geometric functions for textured shape retrieval
Computer Graphics and Computer-Aided Design
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spelling Biasotti, S. Cerri, A. Giorgi, D. Spagnuolo, M. 0167-7055 1467-8659 Wiley Computer Graphics and Computer-Aided Design http://dx.doi.org/10.1111/cgf.12168 <jats:title>Abstract</jats:title><jats:p>In this paper we target the problem of textured 3D object retrieval. As a first contribution, we show how to include photometric information in the persistence homology setting, also proposing a novel theoretical result about multidimensional persistence spaces. As a second contribution, we introduce a generalization of the integral geodesic distance which fuses shape and color properties. Finally, we adopt a purely geometric description based on the selection of geometric functions that are mutually independent. The photometric, hybrid and geometric descriptions are combined into a signature, whose performance is tested on a benchmark dataset.</jats:p> PHOG: Photometric and geometric functions for textured shape retrieval Computer Graphics Forum
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title PHOG: Photometric and geometric functions for textured shape retrieval
title_unstemmed PHOG: Photometric and geometric functions for textured shape retrieval
title_full PHOG: Photometric and geometric functions for textured shape retrieval
title_fullStr PHOG: Photometric and geometric functions for textured shape retrieval
title_full_unstemmed PHOG: Photometric and geometric functions for textured shape retrieval
title_short PHOG: Photometric and geometric functions for textured shape retrieval
title_sort phog: photometric and geometric functions for textured shape retrieval
topic Computer Graphics and Computer-Aided Design
url http://dx.doi.org/10.1111/cgf.12168
publishDate 2013
physical 13-22
description <jats:title>Abstract</jats:title><jats:p>In this paper we target the problem of textured 3D object retrieval. As a first contribution, we show how to include photometric information in the persistence homology setting, also proposing a novel theoretical result about multidimensional persistence spaces. As a second contribution, we introduce a generalization of the integral geodesic distance which fuses shape and color properties. Finally, we adopt a purely geometric description based on the selection of geometric functions that are mutually independent. The photometric, hybrid and geometric descriptions are combined into a signature, whose performance is tested on a benchmark dataset.</jats:p>
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author Biasotti, S., Cerri, A., Giorgi, D., Spagnuolo, M.
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description <jats:title>Abstract</jats:title><jats:p>In this paper we target the problem of textured 3D object retrieval. As a first contribution, we show how to include photometric information in the persistence homology setting, also proposing a novel theoretical result about multidimensional persistence spaces. As a second contribution, we introduce a generalization of the integral geodesic distance which fuses shape and color properties. Finally, we adopt a purely geometric description based on the selection of geometric functions that are mutually independent. The photometric, hybrid and geometric descriptions are combined into a signature, whose performance is tested on a benchmark dataset.</jats:p>
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spelling Biasotti, S. Cerri, A. Giorgi, D. Spagnuolo, M. 0167-7055 1467-8659 Wiley Computer Graphics and Computer-Aided Design http://dx.doi.org/10.1111/cgf.12168 <jats:title>Abstract</jats:title><jats:p>In this paper we target the problem of textured 3D object retrieval. As a first contribution, we show how to include photometric information in the persistence homology setting, also proposing a novel theoretical result about multidimensional persistence spaces. As a second contribution, we introduce a generalization of the integral geodesic distance which fuses shape and color properties. Finally, we adopt a purely geometric description based on the selection of geometric functions that are mutually independent. The photometric, hybrid and geometric descriptions are combined into a signature, whose performance is tested on a benchmark dataset.</jats:p> PHOG: Photometric and geometric functions for textured shape retrieval Computer Graphics Forum
spellingShingle Biasotti, S., Cerri, A., Giorgi, D., Spagnuolo, M., Computer Graphics Forum, PHOG: Photometric and geometric functions for textured shape retrieval, Computer Graphics and Computer-Aided Design
title PHOG: Photometric and geometric functions for textured shape retrieval
title_full PHOG: Photometric and geometric functions for textured shape retrieval
title_fullStr PHOG: Photometric and geometric functions for textured shape retrieval
title_full_unstemmed PHOG: Photometric and geometric functions for textured shape retrieval
title_short PHOG: Photometric and geometric functions for textured shape retrieval
title_sort phog: photometric and geometric functions for textured shape retrieval
title_unstemmed PHOG: Photometric and geometric functions for textured shape retrieval
topic Computer Graphics and Computer-Aided Design
url http://dx.doi.org/10.1111/cgf.12168