Improving Local Symmetry Estimations in RGB-D Images by Fitting Superquadrics

• David Fornas ^[1] ; Pedro J. Sanz ^[1] ; Josep M. Porta ^[2] ; Federico Thomas ^[2]
  1. [1] Universitat Jaume I

     Universitat Jaume I

     Castellón, España

     
  2. [2] UPC-CSIC
• Localización: Actas de las XXXVII Jornadas de Automática: Madrid. 7, 8 y 9 de septiembre de 2016, 2016, ISBN 978-84-9749-808-1, págs. 162-168
• Idioma: inglés
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• Resumen

  • Real-time manipulation tasks rely on finding good candidates for apprehension points which, in turn, usually requires the computation of local symmetries. When RGB-D images are used as input information, these local symmetries can be deduced from segmenting these images and computing geometric moments for each cluster of points. This approach gives a rough approximation because it does not take into account that the considered points lie on a surface. In this paper, to improve the quality of the symmetry estimations, we propose a simple refinement process that takes as input the estimation obtained using moments and then fits a superquadric to the considered set of points. We evaluate our approach on data collected using a Microsoft's Kinect 2 sensor. The obtained experimental results demonstrate the efficacy of the proposed approach.