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Joseph S. B. Mitchell

Researcher at Stony Brook University

Publications -  369
Citations -  14607

Joseph S. B. Mitchell is an academic researcher from Stony Brook University. The author has contributed to research in topics: Approximation algorithm & Polygon. The author has an hindex of 60, co-authored 365 publications receiving 13898 citations. Previous affiliations of Joseph S. B. Mitchell include Statistics Finland & Sandia National Laboratories.

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Efficient collision detection using bounding volume hierarchies of k-DOPs

TL;DR: This work develops and analyzes a method, based on bounding-volume hierarchies, for efficient collision detection for objects moving within highly complex environments, and provides experimental evidence showing that this approach yields substantially faster collision detection than previous methods.
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An efficiently computable metric for comparing polygonal shapes

TL;DR: A method for comparing polygons that is a metric, invariant under translation, rotation, and change of scale, reasonably easy to compute, and intuitive is presented.
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The discrete geodesic problem

TL;DR: An algorithm for determining the shortest path between a source and a destination on an arbitrary (possibly nonconvex) polyhedral surface and generalizes to the case of multiple source points to build the Voronoi diagram on the surface.
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Guillotine Subdivisions Approximate Polygonal Subdivisions: A Simple Polynomial-Time Approximation Scheme for Geometric TSP, k -MST, and Related Problems

TL;DR: In this paper, it was shown that any polygonal subdivision in the plane can be converted into an "m-guillotine" subdivision whose length is at most $(1+{c\over m})$ times that of the original subdivision, for a small constant c. In particular, a consequence of their main theorem is a simple polynomial-time approximation scheme for geometric instances of several network optimization problems, including the Steiner minimum spanning tree, the traveling salesperson problem (TSP), and the k-MST problem.
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Boundary recognition in sensor networks by topological methods

TL;DR: This paper proposes a simple, distributed algorithm that correctly detects nodes on the boundaries and connects them into meaningful boundary cycles, and obtains as a byproduct the medial axis of the sensor field, which has applications in creating virtual coordinates for routing.