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Retrieval and classification methods for textured 3D models: a comparative study

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Abstract

This paper presents a comparative study of six methods for the retrieval and classification of textured 3D models, which have been selected as representative of the state of the art. To better analyse and control how methods deal with specific classes of geometric and texture deformations, we built a collection of 572 synthetic textured mesh models, in which each class includes multiple texture and geometric modifications of a small set of null models. Results show a challenging, yet lively, scenario and also reveal interesting insights into how to deal with texture information according to different approaches, possibly working in the CIELab as well as in modifications of the RGB colour space.

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Acknowledgments

Andrea Cerri, Silvia Biasotti and Michela Spagnuolo were partially supported by the CNR research activity ICT.P10.009; VISIONAIR, European project “FP7 INFRASTRUCTURES” (2011–2015); IQmulus (EU FP7-ICT-2011-318787). Daniela Giorgi was supported by FP7 STREP SEMEOTICONS (Grant No. 611516, 2013–2016). Atsushi Tatsuma and Masaki Aono were supported by Kayamori Foundation of Informational Science Advancement and JSPS KAKENHI Grant Nos. 26280038, 15K12027 and 15K15992.

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Authors and Affiliations

  1. Istituto di Matematica Applicata e Tecnologie Informatiche “E. Magenes”, CNR, Genova, Italy

    S. Biasotti, A. Cerri & M. Spagnuolo

  2. Istituto di Scienza e Tecnologie dell’Informazione “A. Faedo”, CNR, Pisa, Italy

    V. Garro & D. Giorgi

  3. Dipartimento di Informatica, Università di Verona, Verona, Italy

    V. Garro & A. Giachetti

  4. Concordia University, Montreal, Canada

    A. Ben Hamza

  5. National Institute of Standards and Technology, Gaithersburg, USA

    A. Godil & C. Li

  6. Department of Computer Science and Engineering, Toyohashi University of Technology, Toyohashi, Japan

    M. Aono, C. Sanada & A. Tatsuma

  7. Department of Mathematics, National University of Singapore, Singapore, Singapore

    S. Velasco-Forero

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  1. S. Biasotti
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  2. A. Cerri
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Biasotti, S., Cerri, A., Aono, M. et al. Retrieval and classification methods for textured 3D models: a comparative study. Vis Comput 32, 217–241 (2016). https://doi.org/10.1007/s00371-015-1146-3

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