9 research outputs found

    幾つかの画像関連問題の計算複雑度の解析と効率的な解決法の提案

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    金沢大学 / 北陸先端科学技術大学院大学研究課題/領域番号:16092209, 研究期間(年度):2004 - 2007出典:「幾つかの画像関連問題の計算複雑度の解析と効率的な解決法の提案」研究成果報告書 課題番号16092209(KAKEN:科学研究費助成事業データベース(国立情報学研究所)) (https://kaken.nii.ac.jp/ja/grant/KAKENHI-PROJECT-16092209/)を加工して作

    Uniformity of Point Samples in Metric Spaces using Gap Ratio

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    Teramoto et al. defined a new measure of uniformity of point distribution called the \emph{gap ratio} that measures the uniformity of a finite point set sampled from S\cal S, a bounded subset of R2\mathbb{R}^2. We attempt to generalize the definition of this measure over all metric spaces. While they look at online algorithms minimizing the measure at every instance, wherein the final size of the sampled set may not be known a priori, we look at instances in which the final size is known and we wish to minimize the final gap ratio. We solve optimization related questions about selecting uniform point samples from metric spaces; the uniformity is measured using gap ratio. We give lower bounds for specific as well as general instances, prove hardness results on specific metric spaces, and a general approximation algorithm framework giving different approximation ratios for different metric spaces

    Online uniformly inserting points on the sphere

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    Uniformly inserting points on the sphere has been found useful in many scientific and engineering fields. Different from the offline version where the number of points is known in advance, we consider the online version of this problem. The requests for point insertion arrive one by one and the target is to insert points as uniformly as possible. To measure the uniformity we use gap ratio which is defined as the ratio of the maximal gap to the minimal gap of two arbitrary inserted points. We propose a two-phase online insertion strategy with gap ratio of at most 3.69. Moreover, the lower bound of the gap ratio is proved to be at least 1.78

    Uniformity of point samples in metric spaces using gap ratio

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    Teramoto et al. defined a new measure called the gap ratio that measures the uniformity of a finite point set sampled from S\cal S, a bounded subset of R2\mathbb{R}^2. We generalize this definition of measure over all metric spaces by appealing to covering and packing radius. The definition of gap ratio needs only a metric unlike discrepancy, a widely used uniformity measure, that depends on the notion of a range space and its volume. We also show some interesting connections of gap ratio to Delaunay triangulation and discrepancy in the Euclidean plane. The major focus of this work is on solving optimization related questions about selecting uniform point samples from metric spaces; the uniformity being measured using gap ratio. We consider discrete spaces like graph and set of points in the Euclidean space and continuous spaces like the unit square and path connected spaces. We deduce lower bounds, prove hardness and approximation hardness results. We show that a general approximation algorithm framework gives different approximation ratios for different metric spaces based on the lower bound we deduce. Apart from the above, we show existence of coresets for sampling uniform points from the Euclidean space -- for both the static and the streaming case. This leads to a (1+ϵ)\left( 1+\epsilon \right)-approximation algorithm for uniform sampling from the Euclidean space.Comment: 31 pages, 10 figure

    Towards Uniform Online Spherical Tessellations

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    The problem of uniformly placing N points onto a sphere finds applications in many areas. An online version of this problem was recently studied with respect to the gap ratio as a measure of uniformity. The proposed online algorithm of Chen et al. was upper-bounded by 5.99 and then improved to 3.69, which is achieved by considering a circumscribed dodecahedron followed by a recursive decomposition of each face. We analyse a simple tessellation technique based on the regular icosahedron, which decreases the upper-bound for the online version of this problem to around 2.84. Moreover, we show that the lower bound for the gap ratio of placing up to three points is 1+5√2≈1.618 . The uniform distribution of points on a sphere also corresponds to uniform distribution of unit quaternions which represent rotations in 3D space and has numerous applications in many areas

    Towards Uniform Online Spherical Tessellations

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    The problem of uniformly placing points onto a sphere finds applications in many areas. For example, points on the sphere correspond to unit quaternions as well as to the group of rotations SO(3) and the online version of generating uniform rotations (known as “incremental generation”) plays a crucial role in a large number of engineering applications ranging from robotics and aeronautics to computer graphics. An online version of this problem was recently studied with respect to the gap ratio as a measure of uniformity. The first online algorithm of Chen et al. was upper-bounded by 5.99 and later improved to 3.69, which is achieved by considering a circumscribed dodecahedron followed by a recursive decomposition of each face. In this paper we provide a more efficient tessellation technique based on the regular icosahedron, which improves the upper-bound for the online version of this problem, decreasing it to approximately 2.84. Moreover, we show that the lower bound for the gap ratio of placing at least three points is and for at least four points is no less than 1.726.</jats:p

    Towards Uniform Online Spherical Tessellations

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    The problem of uniformly placing N points onto a sphere finds applications in many areas. For example, points on the sphere correspond to unit quaternions as well as to the group of rotations SO(3) and the online version of generating uniform rotations (known as “incremental generation”) plays a crucial role in a large number of engineering applications ranging from robotics and aeronautics to computer graphics. An online version of this problem was recently studied with respect to the gap ratio as a measure of uniformity. The first online algorithm of Chen et al. was upper-bounded by 5.99 and later improved to 3.69, which is achieved by considering a circumscribed dodecahedron followed by a recursive decomposition of each face. In this paper we provide a more efficient tessellation technique based on the regular icosahedron, which improves the upper-bound for the online version of this problem, decreasing it to approximately 2.84. Moreover, we show that the lower bound for the gap ratio of placing at least three points is 1.618 and for at least four points is no less than 1.726

    Collection of abstracts of the 24th European Workshop on Computational Geometry

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    International audienceThe 24th European Workshop on Computational Geomety (EuroCG'08) was held at INRIA Nancy - Grand Est & LORIA on March 18-20, 2008. The present collection of abstracts contains the 63 scientific contributions as well as three invited talks presented at the workshop

    Online Uniformity of Integer Points on a Line

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    This Letter presents algorithms for computing a uniform sequence of n integer points in a given interval [0,m] where m and n are integers such that m>n>0. The uniformity of a point set is measured by the ratio of the minimum gap over the maximum gap. We prove that we can insert n integral points one by one into the interval [0,m] while keeping the uniformity of the point set at least 1/2. If we require uniformity strictly greater than 1/2, such a sequence does not always exist, but we can prove a tight upper bound on the length of the sequence for given values of n and m
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