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Polynomial time approximation schemes for Euclidean traveling salesman and other geometric problems
 Journal of the ACM
, 1998
"... Abstract. We present a polynomial time approximation scheme for Euclidean TSP in fixed dimensions. For every fixed c Ͼ 1 and given any n nodes in 2 , a randomized version of the scheme finds a (1 ϩ 1/c)approximation to the optimum traveling salesman tour in O(n(log n) O(c) ) time. When the nodes ..."
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Cited by 397 (2 self)
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approximation algorithms for all these problems achieved a constantfactor approximation. We also give efficient approximation schemes for Euclidean MinCost Matching, a problem that can be solved exactly in polynomial time. All our algorithms also work, with almost no modification, when distance is measured
Approximation Algorithms for Bipartite and NonBipartite Matching in the Plane
 In SODA: ACMSIAM Symposium on Discrete Algorithms (A Conference on Theoretical and Experimental Analysis of Discrete Algorithms
, 1999
"... In the approximate Euclidean mincost perfect matching problem, we are a given a set V of 2n points in the plane, and a real number " ? 0, and we want to pair up the points (into n pairs) so that the sum of the distances between the paired points is within a multiplicative factor of (1 + " ..."
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Cited by 29 (4 self)
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In the approximate Euclidean mincost perfect matching problem, we are a given a set V of 2n points in the plane, and a real number " ? 0, and we want to pair up the points (into n pairs) so that the sum of the distances between the paired points is within a multiplicative factor of (1
MinCost Multicast Networks in Euclidean Space
"... Abstract—Space information flow is a new field of research recently proposed by Li and Wu [1], [2]. It studies the transmission of information in a geometric space, where information flows can be routed along any trajectories, and can be encoded wherever they meet. The goal is to satisfy given endto ..."
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Cited by 2 (1 self)
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endtoend unicast/multicast throughput demands, while minimizing a natural bandwidthdistance sumproduct (network volume). Space information flow models the design of a blueprint for a minimumcost network. We study the multicast version of the space information flow problem, in Euclidean spaces. We
A DivideandConquer Algorithm for MinCost Perfect Matching in the Plane\Lambda
"... Abstract Given a set V of 2n points in the plane, the mincost perfect matching problem is to pair up the points (into n pairs)so that the sum of the Euclidean distances between the paired points is minimized. We present an O(n3=2 log5 n)time algorithm for computing a mincost perfect matching in ..."
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Abstract Given a set V of 2n points in the plane, the mincost perfect matching problem is to pair up the points (into n pairs)so that the sum of the Euclidean distances between the paired points is minimized. We present an O(n3=2 log5 n)time algorithm for computing a mincost perfect matching
Euclidean reconstruction from uncalibrated views
 Applications of Invariance in Computer Vision
, 1993
"... The possibility of calibrating a camera from image data alone, based on matched points identified in a series of images by a moving camera was suggested by Mayband and Faugeras. This result implies the possibility of Euclidean reconstruction from a series of images with a moving camera, or equivalen ..."
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Cited by 257 (14 self)
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The possibility of calibrating a camera from image data alone, based on matched points identified in a series of images by a moving camera was suggested by Mayband and Faugeras. This result implies the possibility of Euclidean reconstruction from a series of images with a moving camera
Exact Indexing of Dynamic Time Warping
, 2002
"... The problem of indexing time series has attracted much research interest in the database community. Most algorithms used to index time series utilize the Euclidean distance or some variation thereof. However is has been forcefully shown that the Euclidean distance is a very brittle distance me ..."
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Cited by 350 (34 self)
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The problem of indexing time series has attracted much research interest in the database community. Most algorithms used to index time series utilize the Euclidean distance or some variation thereof. However is has been forcefully shown that the Euclidean distance is a very brittle distance
Efficient time series matching by wavelets
 Proc. of 15th Int'l Conf. on Data Engineering
, 1999
"... Time series stored as feature vectors can be indexed by multidimensional index trees like RTrees for fast retrieval. Due to the dimensionality curse problem, transformations are applied to time series to reduce the number of dimensions of the feature vectors. Different transformations like Discrete ..."
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Cited by 286 (1 self)
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. In this paper, we propose to use Haar Wavelet Transform for time series indexing. The major contributions are: (1) we show that Euclidean distance is preserved in the Haar transformed domain and no false dismissal will occur, (2) we show that Haar transform can outperform DFT through experiments, (3) a new
A WeightScaling Algorithm for MinCost Imperfect Matchings in Bipartite Graphs
, 2012
"... Call a bipartite graph G = (X; Y;E) balanced when X = Y. Given a balanced bipartite graph G with edge costs, the assignment problem asks for a perfect matching in G of minimum total cost. The Hungarian Method can solve assignment problems in time O(mn+n 2 log n), where n: = X = Y and m: = ..."
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Cited by 2 (0 self)
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: = E. If the edge weights are integers bounded in magnitude by C> 1, then algorithms using weight scaling, such as that of Gabow and Tarjan, can lower the time to (log(nC)). There are important applications in which G is unbalanced, with X ≠ Y, and we require a mincost matching in G of size r
Multitarget tracking by lagrangian relaxation to mincost network flow
 In CVPR
, 2013
"... We propose a method for global multitarget tracking that can incorporate higherorder track smoothness constraints such as constant velocity. Our problem formulation readily lends itself to path estimation in a trellis graph, but unlike previous methods, each node in our network represents a can ..."
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Cited by 26 (0 self)
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candidate pair of matching observations between consecutive frames. Extra constraints on binary flow variables in the graph result in a problem that can no longer be solved by mincost network flow. We therefore propose an iterative solution method that relaxes these extra constraints using Lagrangian
Results 1  10
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