Slowing down sorting networks to obtain faster sorting algorithms
Journal of the ACM (JACM)
Algorithms on strings, trees, and sequences: computer science and computational biology
Algorithms on strings, trees, and sequences: computer science and computational biology
Algorithms for the Longest Common Subsequence Problem
Journal of the ACM (JACM)
Proceedings of the nineteenth annual symposium on Computational geometry
On map-matching vehicle tracking data
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Computing the Fréchet distance between piecewise smooth curves
Computational Geometry: Theory and Applications
Journal of Mathematical Imaging and Vision
Fréchet distance for curves, revisited
ESA'06 Proceedings of the 14th conference on Annual European Symposium - Volume 14
Dynamic planar map illustration
ACM SIGGRAPH 2007 papers
Dynamics-aware similarity of moving objects trajectories
Proceedings of the 15th annual ACM international symposium on Advances in geographic information systems
Exact algorithms for partial curve matching via the Fréchet distance
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
Shape Matching by Random Sampling
WALCOM '09 Proceedings of the 3rd International Workshop on Algorithms and Computation
Hidden Markov map matching through noise and sparseness
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Map-matching for low-sampling-rate GPS trajectories
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Approximating the Fréchet distance for realistic curves in near linear time
Proceedings of the twenty-sixth annual symposium on Computational geometry
A sensor fusion framework using multiple particle filters for video-based navigation
IEEE Transactions on Intelligent Transportation Systems
Fréchet distance with speed limits
Computational Geometry: Theory and Applications
The frechet distance revisited and extended
Proceedings of the twenty-seventh annual symposium on Computational geometry
Improved algorithms for partial curve matching
ESA'11 Proceedings of the 19th European conference on Algorithms
Path shapes: an alternative method for map matching and fully autonomous self-localization
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Jaywalking your dog: computing the Fréchet distance with shortcuts
Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete Algorithms
Shape matching by random sampling
Theoretical Computer Science
Urban traffic modelling and prediction using large scale taxi GPS traces
Pervasive'12 Proceedings of the 10th international conference on Pervasive Computing
Constructing street networks from GPS trajectories
ESA'12 Proceedings of the 20th Annual European conference on Algorithms
Fast Viterbi map matching with tunable weight functions
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
CrowdAtlas: self-updating maps for cloud and personal use
Proceeding of the 11th annual international conference on Mobile systems, applications, and services
Map matching: comparison of approaches using sparse and noisy data
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
The fréchet distance revisited and extended
ACM Transactions on Algorithms (TALG)
From taxi GPS traces to social and community dynamics: A survey
ACM Computing Surveys (CSUR)
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The subject of this paper are algorithms for measuring the similarity of patterns of line segments in the plane, a standard problem in, e.g., computer vision, geographic information systems, etc. More precisely, we define feasible distance measures that reflect how close a given pattern H is to some part of a larger pattern G. These distance measures are generalizations of the well-known Fréchet distance for curves. We first give an efficient algorithm for the case that H is a polygonal curve and G is a geometric graph. Then, slightly relaxing the definition of distance measure, we give an algorithm for the general case where both, H and G, are geometric graphs.