Journal of Intelligent & Robotic Systems

, Volume 76, Issue 1, pp 35–56 | Cite as

Part-Based Geometric Categorization and Object Reconstruction in Cluttered Table-Top Scenes

Paper Type: Categories (7) and (5)
  • Zoltan-Csaba Marton
  • Ferenc Balint-Benczedi
  • Oscar Martinez Mozos
  • Nico Blodow
  • Asako Kanezaki
  • Lucian Cosmin Goron
  • Dejan Pangercic
  • Michael Beetz
Article

Abstract

This paper presents an approach for 3D geometry-based object categorization in cluttered table-top scenes. In our method, objects are decomposed into different geometric parts whose spatial arrangement is represented by a graph. The matching and searching of graphs representing the objects is sped up by using a hash table which contains possible spatial configurations of the different parts that constitute the objects. Additive feature descriptors are used to label partially or completely visible object parts. In this work we categorize objects into five geometric shapes: sphere, box, flat, cylindrical, and disk/plate, as these shapes represent the majority of objects found on tables in typical households. Moreover, we reconstruct complete 3D models that include the invisible back-sides of objects as well, in order to facilitate manipulation by domestic service robots. Finally, we present an extensive set of experiments on point clouds of objects using an RGBD camera, and our results highlight the improvements over previous methods.

Keywords

Object categorization 3D geometry Part-graph hashing Clutter Domestic robotics 

Mathematics Subject Classifications (2010)

68 60 

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Zoltan-Csaba Marton
    • 1
  • Ferenc Balint-Benczedi
    • 2
  • Oscar Martinez Mozos
    • 3
  • Nico Blodow
    • 4
  • Asako Kanezaki
    • 5
  • Lucian Cosmin Goron
    • 4
  • Dejan Pangercic
    • 6
  • Michael Beetz
    • 2
  1. 1.Institute of Robotics and MechatronicsGerman Aerospace Center (DLR)OberpfaffenhofenGermany
  2. 2.Institute of Artificial IntelligenceUniversität Bremen, Center for Computing Technologies (TZI)BremenGermany
  3. 3.School of Computer ScienceUniversity of LincolnLincolnUK
  4. 4.Intelligent Autonomous SystemsTechnische Universität MünchenMünchenGermany
  5. 5.Machine Intelligence Lab, Deptartment of Mechano-Informatics, Graduate School of Information Science & TechnologyThe University of TokyoTokyoJapan
  6. 6.Autonomous Technologies Group Robert Bosch LLCPalo AltoUSA

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