Mark W. Orletsky

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We present techniques for matching point-sets in two and three dimensions under rigid-body transformations. We prove bounds on the worst-case performance of these algorithms to be within a small constant factor of optimal, and conduct experiments to show that the average performance of these matching algorithms is often better than that predicted by the(More)
We present practical methods for approximate geometric pattern matching in d-dimensions along with experimental data regarding the quality of matches and running times of these methods versus those of a branch-and-bound search. Our methods are faster than previous methods but still produce good matches.
Given a collection S of n line segments in the plane, the planar point location problem is to construct a data structure that can eeciently determine for a given query point p the rst segment(s) in S intersected by vertical rays emanating out from p. It is well known that linear-space data structures can be constructed so as to achieve O(log n) query times.(More)
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