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Praktikum zur Analyse von Formen - Abstandsmaße -

Praktikum zur Analyse von Formen - Abstandsmaße -. Helmut Alt Freie Universität Berlin. Distance functions, Matching. Distance functions d on patterns and shapes measuring their similarity

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Praktikum zur Analyse von Formen - Abstandsmaße -

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  1. Praktikum zur Analyse von Formen- Abstandsmaße - Helmut Alt Freie Universität Berlin

  2. Distance functions, Matching • Distance functions d on patterns and shapes measuring their similarity • Matching two shapes under a certain set of allowable transformations, e.g., translations, rigid motions, similarities, affine transformations: finding the transformation t minimizing the distance between both: • d(t (A),B) = min d(t(A),B) 0 0 t

  3. Hausdorff Distance • Hausdorff distance for sets A,B: d(A,B) = max ( max min ||a-b||, max min ||a-b||) a  A b  B b  B a  A A B

  4. Bad Example for Hausdorff distance

  5. Fréchet distance for parametrized curves a, b: dF(a,b) = inf max ||a(f(t))-b(g(t))|| f,g : [0,1 ] [0,1] t [0,1] where f and g range over continuous non-decreasing reparametrizations. a b Fréchet Distance

  6. b a b a Free Space Diagram • dF(a,b) eiff there is a monotone ascending path in the free space from (0,0) to (1,1) • Monotone path represents a reparametrization of b

  7. b a b a Finding a monotone path in O(mn) time Regions on the boundaries of the cells that can be reached by a monotone path from lower left corner. Find these by traversing cells from bottom to top and from left to right. This algorithm solves the decision problem in O(nm) time. For the computation problem: Binary search on e in O(nmk), where k = # of correct bits Parametric search gives an O(nm log (nm)) algorithm

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