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Testing Landmark Identification Theories in Virtual Environments

  • Denise Peters
  • Yunhui Wu
  • Stephan Winter
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6222)

Abstract

Landmarks are fundamental elements for people to learn an environment. People use these landmarks to enrich their route descriptions (for example, when anchoring movements at decision points). Several automatic landmark identification and selection theories have been suggested in recent years. This paper evaluates these theories by comparing the landmarks identified by automatic landmark selection with landmark choices and behavioral characteristics of human participants moving in a virtual environment. This comparison of automatic selection and human behavior will improve our understanding of automatic landmark identification theories, and will facilitate a weighting of methods for navigation services to generate more human-like route descriptions.

Keywords

Virtual Environment Decision Point Spatial Cognition Short Route Trajectory Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Denise Peters
    • 1
  • Yunhui Wu
    • 2
  • Stephan Winter
    • 2
  1. 1.SFB/TR 8 Spatial CognitionUniversity of BremenGermany
  2. 2.Department of GeomaticsUniversity of MelbourneAustralia

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