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Do You Recognize That Building’s Façade?

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Abstract

With the computational power of modern smartphones constantly increasing, resource intensive applications are becoming feasible to an ever growing extent. In this paper, we report on a research project recently started. Its aim is to develop an application for smartphones that combines pedestrian and public transport navigation including the computation of routes consisting of pedestrian routes and public transport trips and intuitive user guidance at any time of the trip. In particular, we focus on intuitive user guidance based on (LMs) in the surroundings of the user. For this reason, we use collaborative approaches to collect LMs and data about them.

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Notes

  1. A very similar clustering was calculated for the Tourist Guide group, which has been omitted here due to space limitations.

  2. Lynch’s term landmark [15] and salient objects are used interchangeably throughout this work.

  3. [2] applies minor changes to the definition of the concepts, but the basic ideas remain.

References

  1. Testbericht: 7 Navi-Apps für Smartphones im Test. online (2012). http://www.connect.de/testbericht/7-navi-apps-fuer-smartphones-im-test-1238322.html#. Last access on Nov 11th, 2012

  2. Caduff D, Timpf S (2008) On the assessment of landmark salience for human navigation. Cogn Process 9(4):249–267

    Article  Google Scholar 

  3. Chaouali M (2008) Personalisierte Landmarken – Einfluss der Ortskenntnis auf die Auswahl. Master’s thesis, Institut für Kartographie und Geoinformatik, Universität Hannover

  4. Chittaro L, Burigat S (2005) Augmenting audio messages with visual directions in mobile guides: an evaluation of three approaches. In: Proceedings of the 7th international conference on human computer interaction with mobile devices & services, MobileHCI ’05. ACM, New York, pp 107–114

    Chapter  Google Scholar 

  5. Google Inc.: Google maps (2012). https://play.google.com/store/apps/details?id=com.google.android.apps.maps&feature=nav_result#?t=W251bGwsMSwyLDNd. Last access on Feb 12th, 2013

  6. Ishikawa T, Fujiwara H, Imai O, Okabe A (2008) Wayfinding with a gps-based mobile navigation system: a comparison with maps and direct experience. J Environ Psychol 28(1):74–82

    Article  Google Scholar 

  7. Ishikawa T, Nakamura U (2012) Landmark selection in the environment: relationships with object characteristics and sense of direction. Spat Cogn Comput 12(1):1–22

    Google Scholar 

  8. Kato Y, Takeuchi Y (2003) Individual differences in wayfinding strategies. J Environ Psychol 23(2):171–188

    Article  Google Scholar 

  9. Kattenbeck M, Brockelmann M, Hammwöhner R, Jackermeier R, Ludwig B (2013) Vermessungsdaten - OpenStreetMap - In-Situ-Experimente. Die Datengrundlage von URWalking. In: Proceedings of the 13th international symposium of information science, Potsdam, March 19–23, 2013

    Google Scholar 

  10. Klippel A, Winter S (2005) Structural salience of landmarks for route directions. In: Proceedings of the 2005 international conference on spatial information theory. Springer, Berlin, pp 347–362

    Google Scholar 

  11. Kluge M (2009) Fußgängernavigation – Reality View: Entwicklung und Implementierung eines auf erweiterter Realität basierenden Navigationssystems für Fußgänger auf mobilen Geräten. Vermess Brandenbg 2:60–69

    Google Scholar 

  12. Köpke J (2007) Personalisierte Landmarken. Master’s thesis, Institut für Kartographie und Geoinformatik, Universität Hannover

  13. Kreuzpointner L, Lukesch H (2013) (LPS-2). Leistungsprüfsystem 2. Hogrefe, Göttingen

  14. Lübke C (2004) Extraktion von Landmarken aus ATKIS-Daten. Master’s thesis, Institut für Kartographie und Geoinformatik, Universität Hannover

  15. Lynch K (1960) The image of the city. MIT Press, Cambridge

    Google Scholar 

  16. Muenzer S, Hoelscher C (2011) Development and validation of a self-report measure of environmental spatial strategies. Diagnostica 57(3):111–125

    Article  Google Scholar 

  17. Pielot M, Boll S (2010) In fifty metres turn left: why turn by turn instructions fail pedestrians. In: Proceedings of HaptiMap, workshop at MobileHCI. ACM, New York, pp 26–28

    Google Scholar 

  18. Raubal M, Winter S (2002) Enriching wayfinding instructions with local landmarks. In: Egenhofer M, Mark D (eds) Geographic information science. Lecture notes in computer science, vol 2478. Springer, Berlin, pp 243–259

    Chapter  Google Scholar 

  19. Rümelin S, Rukzio E, Hardy R (2011) Naviradar: a novel tactile information display for pedestrian navigation. In: Proceedings of the 24th annual ACM symposium on user interface software and technology, UIST ’11. ACM, New York, pp 293–302

    Google Scholar 

  20. Stark A, Riebeck M, Kawalek J (2007) How to design an advanced pedestrian navigation system: field trial results. In: 4th IEEE workshop on intelligent data acquisition and advanced computing systems: technology and applications. IDAACS 2007, pp 690–694

    Chapter  Google Scholar 

  21. WiFiSLAM Inc.: Wifislam (2013). http://www.wifislam.com/#/home. Last access Feb 13th, 2013

  22. Winter S (2003) Route adaptive selection of salient features. In: Kuhn W, Worboys M, Timpf S (eds) Spatial information theory. Foundations of geographic information science. Lecture notes in computer science, vol 2825. Springer, Berlin, pp 349–361

    Chapter  Google Scholar 

  23. Winter S, Raubal M, Nothegger C (2004) Focalizing measures of salience for wayfinding. In: Meng L, Reichenbacher ZAT (eds) Map-based mobile services: theories, methods, and design implementations, Springer geosciences, pp 127–142

    Google Scholar 

  24. Small worlds: stadtführung regensburg (2013). https://play.google.com/store/apps/details?id=de.smallworlds.cityguide&feature=search_result#?t=W251bGwsMSwxLDEsImRlLnNtYWxsd29ybGRzLmNpdHlndWlkZSJd. Last access on Feb 12th, 2013

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Acknowledgements

NADINE is funded by the German Federal Ministry of Economics and Technology (BMWIi) under grant no. 19 P 12009 F.

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Correspondence to Bernd Ludwig.

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Ludwig, B., Bienk, S., Kattenbeck, M. et al. Do You Recognize That Building’s Façade?. Künstl Intell 27, 241–246 (2013). https://doi.org/10.1007/s13218-013-0253-4

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