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3D Model Selection from an Internet Database for Robotic Vision (bibtex)
  author = {Klank, Ulrich and Zia, Muhammad Zeeshan and Beetz, Michael},
  title = {{3D} Model Selection from an Internet Database for Robotic Vision},
  booktitle = {International Conference on Robotics and Automation ({ICRA)}},
  year = {2009},
  pages = {2406–2411},
  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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Last edited 29.01.2013 17:37 by Quirin Lohr