References
- M.A. Abam, M. de Berg, P. Hachenberger, and A. Zarei, Streaming algorithms for line simplification, Discrete Comput. Geom. 43 (2010), pp. 497–515.
- P.K. Agarwal, S. Har-Peled, N.H. Mustafa, and Y. Wang, Near-linear time approximation algorithms for curve simplification, Algorithmica 42 (2005), pp. 203–219.
- B. Aronov, P. Bose, E.D. Demaine, J. Gudmundsson, J. Iacono, S. Langerman, and M.H.M. Smid, Data structures for halfplane proximity queries and incremental voronoi diagrams, Algorithmica 80 (2018), pp. 3316–3334.
- L. Buzer, Optimal simplification of polygonal chain for rendering, in Symposium on Computational Geometry (SoCG), Gyeongju, South Korea, 2007, pp. 168–174.
- W. Cao and Y. Li, Dots – an online and near-optimal trajectory simplification algorithm, J. Syst. Softw. 126 (2017), pp. 34–44.
- W.S. Chan and F. Chin, Approximation of polygonal curves with minimum number of line segments or minimum error, Int. J. Comput. Geom. Appl. 6 (1996), pp. 59–77.
- D.Z. Chen and O. Daescu, Space-efficient algorithms for approximating polygonal curves in two-dimensional space, Int. J. Comput. Geom. Appl. 13 (2003), pp. 95–111.
- M. Chen, M. Xu, and P. Fränti, A fast o(n) multiresolution polygonal approximation algorithm for gps trajectory simplification, IEEE Trans. Image Process. 21 (2012), pp. 2770–2785.
- D.H. Douglas and T.K. Peucker, Algorithms for the reduction of the number of points required to represent a digitized line or its caricature, Cartographica 10 (1973), pp. 112–122.
- L.J. Guibas, J. Hershberger, J.S.B. Mitchell, and J. Snoeyink, Approximating polygons and subdivisions with minimum link paths, Int. J. Comput. Geom. Appl. 3 (1993), pp. 383–415.
- J. Hershberger and J. Snoeyink, An O(nlogn) implementation of the Douglas-Peucker algorithm for line simplification, in Annual ACM Symposium on Computational Geometry (SoCG), ACM, 1994, pp. 383–384.
- J. Hershberger and J. Snoeyink, Cartographic line simplification and polygon CSG formulae and in O(nlog∗n) time, in International Workshop on Algorithms and Data Structures, Springer, 1997, pp. 93–103.
- H. Imai and M. Iri, Computational-geometric methods for polygonal approximations of a curve, Comput. Vis. Graph. Image Process. 36 (1986), pp. 31–41.
- H. Imai and M. Iri, Polygonal approximations of a curve – formulations and algorithms, in Computational Morphology: A Computational Geometric Approach to the Analysis of Form, G.T. Toussaint, ed., North-Holland, 1988, pp. 71–86.
- H.V. Jagadish, C. Long, and R.C.-W. Wong, Direction-preserving trajectory simplification, PVLDB6 (2013), pp. 949–960.
- X. Lin, S. Ma, H. Zhang, T. Wo, and J. Huai, One-pass error bounded trajectory simplification, PVLDB 10 (2017), pp. 841–852.
- A. Melkman and J. O'Rourke, On polygonal chain approximation, in Computational Morphology: A Computational Geometric Approach to the Analysis of Form, G.T. Toussaint, ed., North-Holland, 1988, pp. 87–95.
- J. Muckell, P.W. Olsen, J.H. Hwang, C.T. Lawson, and S.S. Ravi, Compression of trajectory data – a comprehensive evaluation and new approach, GeoInformatica 18 (2017), pp. 435–460.
- M. van de Kerkhof, I. Kostitsyna, M. Löffler, M. Mirzanezhad, C. Wenk, Global curve simplification, in European Symposium on Algorithms (ESA), Munich/Garching, Germany, 2019, pp. 67:1–67:14.
- M.J. van Kreveld, M. Löffler, L. Wiratma, On optimal polyline simplification using the Hausdorff and Fréchet distance, in Symposium on Computational Geometry (SoCG),Budapest, Hungary , 2018, pp. 56:1–56:14.
- D. Zhang, M. Ding, D. Yang, Y. Liu, J. Fan, and H.T. Shen, Trajectory simplification – an experimental study and quality analysis, Proc. VLDB Endow. 11 (2018), pp. 934–946.