Advertisement

Semantic Trajectory Compression

  • Falko Schmid
  • Kai-Florian Richter
  • Patrick Laube
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5644)

Abstract

In the light of rapidly growing repositories capturing the movement trajectories of people in spacetime, the need for trajectory compression becomes obvious. This paper argues for semantic trajectory compression (STC) as a means of substantially compressing the movement trajectories in an urban environment with acceptable information loss. STC exploits that human urban movement and its large–scale use (LBS, navigation) is embedded in some geographic context, typically defined by transportation networks. STC achieves its compression rate by replacing raw, highly redundant position information from, for example, GPS sensors with a semantic representation of the trajectory consisting of a sequence of events. The paper explains the underlying principles of STC and presents an example use case.

Keywords

Trajectories Moving Objects Semantic Description Data Compression 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Li, X., Lin, H.: Indexing network-constrained trajectories for connectivity-based queries. Int. Journal of Geographical Information Science 20(3), 303–328 (2006)CrossRefGoogle Scholar
  2. 2.
    Alvares, L.O., Bogorny, V., Kuijpers, B., Fernandes de Macedo, J.A., Moelans, B., Vaisman, A.: A model for enriching trajectories with semantic geographical information. In: GIS 2007: Proc. of the 15th annual ACM international symposium on Advances in GIS, pp. 1–8. ACM, New York (2007)Google Scholar
  3. 3.
    Spaccapietra, S., Parent, C., Damiani, M.L., de Macedo, J.A., Portoa, F., Vangenot, C.: A conceptual view on trajectories. Data and Knowledge Engineering 65(1), 126–146 (2008)CrossRefGoogle Scholar
  4. 4.
    Tversky, B., Lee, P.U.: How space structures language. In: Freksa, C., Habel, C., Wender, K.F. (eds.) Spatial Cognition 1998. LNCS (LNAI), vol. 1404, pp. 157–175. Springer, Heidelberg (1998)CrossRefGoogle Scholar
  5. 5.
    Klippel, A., Hansen, S., Richter, K.F., Winter, S.: Urban granularities – a data structure for cognitively ergonomic route directions. GeoInformatica 13(2), 223–247 (2009)CrossRefGoogle Scholar
  6. 6.
    Richter, K.F.: Context-Specific Route Directions - Generation of Cognitively Motivated Wayfinding Instructions. DisKI, vol. 314. IOS Press, Amsterdam (2008); also appeared as SFB/TR 8 Monographs Volume 3Google Scholar
  7. 7.
    Schmid, F.: Knowledge based wayfinding maps for small display cartography. Journal of Location Based Services 2(1), 57–83 (2008)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Falko Schmid
    • 1
  • Kai-Florian Richter
    • 1
  • Patrick Laube
    • 2
  1. 1.Transregional Collaborative Research Center SFB/TR 8 Spatial CognitionUniversity of BremenBremenGermany
  2. 2.Department of GeomaticsThe University of MelbourneAustralia

Personalised recommendations