8,136 research outputs found

    On the Area of Overlap of Translated Polygons

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    (Also cross-referenced as CAR-TR-699) Given two simple polygons P and Q in the plane and a translation vector t E R2, the area-oJ-overlap function of P and Q is the function Ar(t) = Area(P n (t + Q)), where t + Q denotes Q translated by t. This function has a number of applications in areas such as motion planning and object recognition. We present a number of mathematical results regarding this function. We also provide efficient algorithms for computing a representation of this function, and for tracing contour curves of constant area of o verlap

    Approximating the Maximum Overlap of Polygons under Translation

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    Let PP and QQ be two simple polygons in the plane of total complexity nn, each of which can be decomposed into at most kk convex parts. We present an (1−ε)(1-\varepsilon)-approximation algorithm, for finding the translation of QQ, which maximizes its area of overlap with PP. Our algorithm runs in O(cn)O(c n) time, where cc is a constant that depends only on kk and ε\varepsilon. This suggest that for polygons that are "close" to being convex, the problem can be solved (approximately), in near linear time

    Probabilistic Matching of Planar Regions

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    We analyze a probabilistic algorithm for matching shapes modeled by planar regions under translations and rigid motions (rotation and translation). Given shapes AA and BB, the algorithm computes a transformation tt such that with high probability the area of overlap of t(A)t(A) and BB is close to maximal. In the case of polygons, we give a time bound that does not depend significantly on the number of vertices

    Solving Irregular Strip Packing Problems With Free Rotations Using Separation Lines

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    Solving nesting problems or irregular strip packing problems is to position polygons in a fixed width and unlimited length strip, obeying polygon integrity containment constraints and non-overlapping constraints, in order to minimize the used length of the strip. To ensure non-overlapping, we used separation lines. A straight line is a separation line if given two polygons, all vertices of one of the polygons are on one side of the line or on the line, and all vertices of the other polygon are on the other side of the line or on the line. Since we are considering free rotations of the polygons and separation lines, the mathematical model of the studied problem is nonlinear. Therefore, we use the nonlinear programming solver IPOPT (an algorithm of interior points type), which is part of COIN-OR. Computational tests were run using established benchmark instances and the results were compared with the ones obtained with other methodologies in the literature that use free rotation
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