Recognition and Tracking of 3D Objects by 1D Search
نویسندگان
چکیده
We show that the bounded error recognition problem for images of non-planar 3D objects using point features can be decomposed into 1D search tasks, along lines joining the origin of the object coordinate system to the feature points chosen to model the object. Points are constructed along these lines at locations given by the coordinates of the detected image points; concurrent bracketing of these points by segment tree search along each of these lines provides maximal matchings between feature points and image points. Depth of search is limited by pixel resolution. This method is well adapted to the task of tracking objects in the presence of variable occlusions and clutter.
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