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Fast vision-based minimum distance determination between known and unkown objects
Kuhn, Stefan; Henrich, Dominik;
Intelligent Robots and Systems, 2007. IROS 2007. IEEE/RSJ International Conference on
Oct. 29 2007-Nov. 2 2007
Page(s):2186
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2191
Abstract:
We present a method for quickly determin- ing the minimum distance between multiple known and multi- ple unkown objects within a camera image. Known objects are objects with known geometry, position, orientation, and con- figuration. Unkown objects are objects which have to be de- tected 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.
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