PHOG: photometric and geometric functions for textured shape retrieval

  • Authors:
  • S. Biasotti;A. Cerri;D. Giorgi;M. Spagnuolo

  • Affiliations:
  • Istituto di Matematica Applicata e Tecnologie Informatiche "E. Magenes", CNR, Italy;Istituto di Matematica Applicata e Tecnologie Informatiche "E. Magenes", CNR, Italy;Istituto di Scienza e Tecnologie dell'Informazione "A. Faedo", CNR, Italy;Istituto di Matematica Applicata e Tecnologie Informatiche "E. Magenes", CNR, Italy

  • Venue:
  • SGP '13 Proceedings of the Eleventh Eurographics/ACMSIGGRAPH Symposium on Geometry Processing
  • Year:
  • 2013

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Abstract

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.