Motivated by an application in automated manufacturing, the present thesis studies optimization problems arising in several areas of computer vision. We investigate the largest common point set measure in Euclidean space, the computation of the Gromov-Hausdorff distance of metric spaces, and the dense k-subgraph problem. A mathematical analysis of these problems yields computational complexity results as well as algorithms which permit an approximate solution of large instances that cannot be solved by traditional methods.
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Motivated by an application in automated manufacturing, the present thesis studies optimization problems arising in several areas of computer vision. We investigate the largest common point set measure in Euclidean space, the computation of the Gromov-Hausdorff distance of metric spaces, and the dense k-subgraph problem. A mathematical analysis of these problems yields computational complexity results as well as algorithms which permit an approximate solution of large instances that cannot be so...
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