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Fast Vision-Based Minimum Distance Determination Between Known and Unknown Objects
Stefan Kuhn , Dominik Henrich

Abstract (english)
We present a method for quickly determining the minimum distance between multiple known and multiple unkown objects within a camera image. Known objects are objects with known geometry, position, orientation, and configuration. Unkown objects are objects which have to be detected by a vision sensor but with unkown geometry, position, orientation and configuration. The known objects are modeled and expanded in 3D and then projected into a camera image. The camera image is classified into object areas including known and unknown objects and into non-object areas. The distance is conservatively estimated by searching for the largest expansion radius where the projected model does not intersect the object areas classified as unknown in the camera image. The method requires only minimal computation times and can be used for surveillance and safety applications.

Publication data

Year: 2007
Publication date: 31. October 2007
Place: San Diego/USA
Source: 2007 IEEE International Conference on Intelligent Robots and Systems, San Diego/USA
Project: SIMERO
Keywords (deutsch): Mensch-Roboter-Koexistenz , Mensch-Roboter-Kooperation
Keywords (english): Human-Robot-Coexistence , Human-Robot-Cooperation , vision
Referrer: http://www.ai3.uni-bayreuth.de/resypub/?mode=pub_show&pub_ref=kuhn2007a

BibTeX

@ARTICLE{kuhn2007a,
  TITLE             = "Fast Vision-Based Minimum Distance Determination Between Known and Unknown Objects",
  AUTHOR            = "Kuhn, Stefan and Henrich, Dominik",
  YEAR              = "2007",
  JOURNAL           = "2007 IEEE International Conference on Intelligent Robots and Systems, San Diego/USA",
  HOWPUBLISHED      = "\url{http://www.ai3.uni-bayreuth.de/resypub/?mode=pub_show&pub_ref=kuhn2007a}",
}

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kuhn2007a.Fast.VisionBased.Minimum.Distance.Determination.Between.Known.and.Unknown.Objects.pdf   1006.8K   english   PDF   download preprint


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