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Salient Spin Images: A Descriptor for 3D Object Recognition

  • Jihad H’rouraEmail author
  • Michaël Roy
  • Alamin Mansouri
  • Driss Mammass
  • Patrick Juillion
  • Ali Bouzit
  • Patrice Méniel
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10884)

Abstract

In the last decades a wide range of algorithms have been devoted to recognize 3D free-from objects under real conditions such as occlusions, clutters, rotation, scale and translation. Spin image is one of these algorithms known to be robust to rotation, translation, occlusions up to 70% and clutters up to 60%, but still suffer from scaling, resolution changes and it is time consuming. In this paper we present a novel approach based on spin images, called salient spin images (SSI). This method enhances spin images algorithm based on its limits. Particularly, it decreases significantly the complexity of the algorithm using DoG detector, it shows a higher performance due to the relevant localization of salient vertices on the scene, and its robustness to occlusions reaches 80%.

Keywords

3D object recognition Salient vertex spin image DoG Clutter Occlusion True positives 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Jihad H’roura
    • 1
    Email author
  • Michaël Roy
    • 2
  • Alamin Mansouri
    • 2
  • Driss Mammass
    • 1
  • Patrick Juillion
    • 2
  • Ali Bouzit
    • 1
  • Patrice Méniel
    • 3
  1. 1.IRF-SIC LaboratoryIbn Zohr UniversityAgadirMorocco
  2. 2.LE2IUniversité de Bourgogne Franche-ComtéAuxerreFrance
  3. 3.ARTEHISUniversité de Bourgogne Franche-ComtéDijonFrance

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