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Robust Pose Estimation for Outdoor Mixed Reality with Sensor Fusion

  • ZhiYing Zhou
  • Jayashree Karlekar
  • Daniel Hii
  • Miriam Schneider
  • Weiquan Lu
  • Stephen Wittkopf
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5616)

Abstract

We present a sensor fusion based technique for outdoor augmented reality system for mobile devices using GPS, gyroscope, and geo-referenced 3D models of the urban environment. Geo-spatial interaction not only provides overlays of the existing environment but compliments with other data such as location-specific photos, videos and other information from different time periods enhancing the overall user experience of augmented reality. To provide robust pose estimation of the camera relative to the world coordinates, firstly, GPS and gyroscope are used to obtain the rough estimation. Secondly, model based silhouette tracking and sensor fusion approach is used to refine the rough estimation and to provide seamless media rich augmentation of 3D textured models.

Keywords

Mobile Device Virtual Reality Augmented Reality Inertial Sensor Sensor Fusion 
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 2009

Authors and Affiliations

  • ZhiYing Zhou
    • 1
  • Jayashree Karlekar
    • 1
  • Daniel Hii
    • 1
  • Miriam Schneider
    • 1
  • Weiquan Lu
    • 1
  • Stephen Wittkopf
    • 1
  1. 1.Interactive Multimedia Lab, Department of Electrical Computer Engineering, Department of ArchitectureNational University of SingaporeSingapore

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