3D Model Selection from an Internet Database for Robotic Vision (bibtex)
by Ulrich Klank, Muhammad Zeeshan Zia, Michael Beetz
Abstract:
We propose a new method for automatically accessing an internet database of 3D models that are searchable only by their user-annotated labels, for using them for vision and robotic manipulation purposes. Instead of having only a local database containing already seen objects, we want to use shared databases available over the internet. This approach while having the potential to dramatically increase the visual recognition capability of robots, also poses certain problems, like wrong annotation due to the open nature of the database, or overwhelming amounts of data (many 3D models) or the lack of relevant data (no models matching a specified label). To solve those problems we propose the following: First, we present an outlier/inlier classification method for reducing the number of results and discarding invalid 3D models that do not match our query. Second, we utilize an approach from computer graphics, the so called 'morphing', to this application to specialize the models, in order to describe more objects. Third, we search for 3D models using a restricted search space, as obtained from our knowledge of the environment. We show our classification and matching results and finally show how we can recover the correct scaling with the stereo setup of our robot.
Reference:
Ulrich Klank, Muhammad Zeeshan Zia, Michael Beetz, "3D Model Selection from an Internet Database for Robotic Vision", In International Conference on Robotics and Automation (ICRA), pp. 2406-2411, 2009.
Bibtex Entry:
@InProceedings{klank09icra,
  author	= {Ulrich Klank and Muhammad Zeeshan Zia and Michael Beetz},
  title		= {{3D Model Selection from an Internet Database for Robotic Vision}},
  booktitle	= {International Conference on Robotics and Automation (ICRA)},
  year		= {2009},
  pages =   {2406--2411},
  bib2html_pubtype = {Conference Paper},
  bib2html_rescat  = {Models},
  bib2html_groups  = {Cop},
  bib2html_funding  = {CoTeSys},
  bib2html_domain  = {Assistive Household},
  abstract 	= {We propose a new method for automatically accessing an internet
                   database of 3D models that are searchable only by their
                   user-annotated labels, for using them for vision and robotic
                   manipulation purposes. Instead of having only a local database
                   containing already seen objects, we want to use shared databases
                   available over the internet. This approach while having the
                   potential to dramatically increase the visual recognition capability
                   of robots, also poses certain problems, like wrong annotation due to
                   the open nature of the database, or overwhelming amounts of data
                   (many 3D models) or the lack of  relevant data (no models matching a
                   specified label). To solve those problems we propose the following:
                   First, we present an outlier/inlier classification method for
                   reducing the number of results and discarding invalid 3D models that
                   do not match our query. Second, we utilize an approach from computer
                   graphics, the so called 'morphing', to this application to
                   specialize the models, in order to describe more objects. Third, we
                   search for 3D models using a restricted search space, as obtained
                   from our knowledge of the environment. We show our classification
                   and matching results and finally show how we can recover the correct
                   scaling with the stereo setup of our robot.}
}
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