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Combining 3D Shape and Color for 3D Object Recognition

  • Susana BrandãoEmail author
  • João P. Costeira
  • Manuela Veloso
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9730)

Abstract

We present new results in object recognition based on color and 3D shape obtained from 3D cameras. Namely, we further exploit diffusion processes to represent shape and the use of color/texture as a perturbation to the diffusion process. Diffusion processes are an effective tool to replace shortest path distances in the characterization of 3D shapes. They also provide effective means for the seamlessly representation of color and shape, mainly because they provide information both the color and on their distribution over surfaces. While there have been different approaches for incorporating color information in the diffusion process, this is the first work that explores different parameterizations of color and their impact on recognition tasks. We present results using very challenging datasets, where we propose to recognize different instances of the same object class assuming a very limited a-priori knowledge on each individual object.

Keywords

Heat Kernel Library Size Partial View Precision Result Instant Noodle 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Susana Brandão
    • 1
    Email author
  • João P. Costeira
    • 1
  • Manuela Veloso
    • 2
  1. 1.Instituto Superior TécnicoLisboaPortugal
  2. 2.Carnegie Mellon UniversityPittsburghUSA

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