| M. Godau. A natural metric for curves: Computing the distance for polygonal chains and approximation algorithms. In Proc. of the 8th Annual Symposium on Theoretical Aspects of Computer Science, pages 127-136, 1991. |
....k nearest neighbor analysis, but not for ranking purposes. Of the few metrics that have been proposed, one of the most popular has been the Hausdorff distance metric (e.g. Huttenlocher et al. 19] While it may not be the best metric for comparing arbitrary polygonal curves (Godau [14] and Alt and Godau [2] it is well suited for simple polygonal shapes. 5. THE HAUSDORFF DISTANCE METRIC Following Huttenlocher et al. 19] we can model two photometric distributions as finite point sets = and = The Hausdorff distance is then defined as: A B h B A h B A ....
Godau, M. 1991. "A Natural Metric for Curves -- Computing the Distance for Polygonal Chains and Approximation Algorithms," Lecture Notes in Computer Science 480: STACS 91 (Eighth Annual Symposium on Theoretical Aspects of Computer Science). C. Choffrut and M. Jantzen, Eds. New York, NY: Springer-Verlag, pp. 127-136.
....makes use of a sorting network with very high constants in the running time. A simpler sorting algorithm leads to an asymptotic running time of ######## ### # #. Still, the parametric search is not easy to implement. A simpler algorithm, which runs in time ###### # ## ######## is given in [20]. A variation of the Frechet distance is obtained by dropping the monotonicity condition of the parameterization. The resulting Frechet distance #### ## is a semimetric: zero distance need not mean that the objects are the same. Another variation is to consider partial matching: finding the part ....
M. Godau. A natural metric for curves - computing the distance for polygonal chains and approximation algorithms. In Proceedings of the Symposium on Theoretical Aspects of Computer Science (STACS), Lecture Notes in Computer Science 480, pages 127--136. Springer, 1991.
.... to whether there exists a continuous and monotone curve in the free space of I u Theta I v from (u s ; v s ) to (u e ; v e ) The Frechet distance between curves can be computed analytically in the case that c 1 (u) and c 2 (v) are both polygonal curves (i.e. piecewise linear) Alt and Godau [2, 34] give algorithms for determining the Frechet distance between polygonal curves assuming the two curves have linear parametrizations and unit length parametric intervals for each 22 segment. Assuming P and Q are two such curves, each consisting of a single segment, they show that the free space for ....
Godau, M. A natural metric for curves -- computing the distance for polygonal chains and approximation algorithms. In STACS 91. 8th Annual Symposium on Theoretical Aspects of Computer Science Proceedings (Hamburg, Germany, 14-16 February 1991), C. Choffrut and M. Jantzen, Eds., Springer-Verlag; Berlin, Germany, pp. 127--136.
....here makes use of a sorting network with very high constants in the running time. A simpler sorting algorithm leads to an asymptotic running time of O(mn(log mn) 3 ) Still, the parametric search is not easy to implement. A simpler algorithm, which runs in time O(mn(m n) log(mn) is given in [God91] A variation of the Fr echet distance is obtained by dropping the monoticity condition of the parameterization. The resulting Fr echet distance d(A; B) is a semimetric: zero distance need not mean that the objects are the same, see Section 3. For this the decision problem, deciding whether d(A; ....
M. Godau. A natural metric for curves - computing the distance for polygonal chains and approximation algorithms. In Proceedings of the Symposium on Theoretical Aspects of Computer Science (STACS), Lecture Notes in Computer Science 480, pages 127-136. Springer, 1991.
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M. Godau. A natural metric for curves: Computing the distance for polygonal chains and approximation algorithms. In Proc. of the 8th Annual Symposium on Theoretical Aspects of Computer Science, pages 127-136, 1991.
No context found.
M. Godau. A natural metric for curves { computing the distance for polygonal chains and approximation algorithms. In Proc. 8th Sympos. Theor. Aspects of Comp. STACS, LNCS vol. 480, pages 127-136, 1991.
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