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Point Pattern Matching

2003; Ukkonen, Lemström, Mäkinen

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Encyclopedia of Algorithms

Keywords and Synonyms

Point set matching; Geometric matching; Geometric alignment; Largest common point set        

Problem Definition

Let ℝ denote the set of reals and ℝd the d-dimensional real space. A finite subset of \( \mathbb{R}^d \) is called a point set. The set of all point sets (subsets of \( \mathbb{R}^d \)) is denoted \( \mathcal{P}(\mathbb{R}^d) \).

Point pattern matching problems ask for finding similarities between point sets under some transformations. In the basic set–up a target point set \( {T \subset \mathbb{R}^d} \) and a pattern point set (point pattern) \( {P \subset \mathbb{R}^d} \) are given, and the problem is to locate a subset I of T (if it exists) such that P matches I. Matching here means that P becomes exactly or approximately equal to I when a transformation from a given set \( \mathcal{F} \) of transformations is applied on P.

Set \( \mathcal{F} \) can be, for example, the set of all translations (a constant vector added to each point in P), or all...

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Recommended Reading

  1. Akutsu, T., Kanaya, K., Ohyama, A., Fujiyama, A.: Point matching under non-uniform distortions. Discret. Appl. Math. 127, 5–21 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  2. Alt, H., Guibas, L.: Discrete geometric shapes: Matching, interpolation, and approximation. In: Sack, J.R., Urrutia, J. (eds.) Handbook of Computational Geometry, pp. 121–153. Elsevier Science Publishers B.V. North-Holland, Amsterdam (1999)

    Google Scholar 

  3. Alt, H., Mehlhorn, K., Wagener, H., Welzl, E.: Congruence, similarity and symmetries of geometric objects. Discret. Comput. Geom. 3, 237–256 (1988)

    Article  MathSciNet  MATH  Google Scholar 

  4. Atkinson, M.D.: An optimal algorithm for geometric congruence. J. Algorithms 8, 159–172 (1997)

    Article  Google Scholar 

  5. Barequet, G., Har-Peled, S.: Polygon containment and translational min‐hausdorff‐distance between segment sets are 3SUM-hard. Int. J. Comput. Geom. Appl. 11(4), 465–474 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  6. Böcker, S., Mäkinen, V.: Maximum line-pair stabbing problem and its variations. In: Proc. 21st European Workshop on Computational Geometry (EWCG'05), pp. 183–186. Technische Universität Eindhoven, The Netherlands (2005)

    Google Scholar 

  7. Brass, P., Pach, J.: Problems and results on geometric patterns. In: Avis, D. et al. (eds.) Graph Theory and Combinatorial Optimization, pp. 17–36. Springer Science + Business Media Inc., NY, USA (2005)

    Google Scholar 

  8. Chew, L.P., Kedem, K.: Improvements on geometric pattern matching problems. In: Proc. Scandinavian Workshop Algorithm Theory (SWAT). LNCS, vol. 621, pp. 318–325. Springer, Berlin (1992)

    Google Scholar 

  9. Choi, V., Goyal, N.: An efficient approximation algorithm for point pattern matching under noise. In: Proc. 7th Latin American Symposium on Theoretical Informatics (LATIN 2006). LNCS, vol. 3882, pp. 298–310. Springer, Berlin (2006)

    Google Scholar 

  10. Clifford, R., Christodoukalis, M., Crawford, T., Meredith, D., Wiggins, G.: A Fast, Randomised, Maximum Subset Matching Algorithm for Document-Level Music Retrieval. In: Proc. International Conference on Music Information Retrieval (ISMIR 2006), University of Victoria, Canada (2006)

    Google Scholar 

  11. Efrat, A., Itai, A., Katz, M.: Geometry Helps in Bottleneck Matching and Related Problems. Algorithmica 31(1), 1–28 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  12. Mäkinen, V., Ukkonen, E.: Local Similarity Based Point-Pattern Matching. In: Proc. 13th Annual Symposium on Combinatorial Pattern Matching (CPM 2002). LNCS, vol. 2373, pp. 115–132. Springer, Berlin (2002)

    Google Scholar 

  13. Ukkonen, E., Lemström, K., Mäkinen, V.: Sweepline the music! In: Klein, R. Six, H.W., Wegner, L. (eds.) Computer Science in Perspective, Essays Dedicated to Thomas Ottmann. LNCS, vol. 2598, pp. 330–342. Springer (2003)

    Google Scholar 

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Mäkinen, V., Ukkonen, E. (2008). Point Pattern Matching. In: Kao, MY. (eds) Encyclopedia of Algorithms. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-30162-4_296

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