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Hausdorff Distance under Translation for Points, Disks, and Balls (2002)
| Content Provider | CiteSeerX |
|---|---|
| Author | Agarwal, Pankaj K. Sharir, Micha Wang, Yusu Har-Peled, Sariel |
| Abstract | Let A and B be two sets of balls in R^d, d = 2, 3. We measure similarity between A and B by computing the minimum Hausdorff distance between A+t and B, where the minimum is taken either over all vectors t &in R^d or over the vectors t such that A+t and B do not intersect. These problems arise in measuring similarity between the shapes of two proteins. We propose a number of exact and approximation algorithms for these problems. Since Hausdorff distance is sensitive to outliers, we also propose efficient approximation algorithms for computing the minimum root-mean-square (rms) Hausdorff distance, under translation, between two point sets. |
| File Format | |
| Publisher Date | 2002-01-01 |
| Access Restriction | Open |
| Subject Keyword | Efficient Approximation Algorithm Point Set Approximation Algorithm Minimum Root-mean-square Minimum Hausdorff Distance Hausdorff Distance |
| Content Type | Text |
