Vision will be increasingly important in robotics applications. An object is modeled by critical curves extracted from the object. In the simplest case the object's curve is its outline. A solution to the curve partitioning problem is shown for nonconvex objects. Curves are described in a rotation and translation invariant way. A way to build a combined model database of many classes of objects is presented. A test to insure disjointness of model classes is given. An efficient technique for computing a network of these curves from a gray-level frame is presented. A graph algorithm is presented to match the model in an efficient way, independent of the scaling found in the scene. A technique for computing and classifying more general critical curves from three-dimensional data is developed.
['J. Stenstrom']
Syntactic pattern recognition for robot vision