“Anywhere Augmentation”: Towards Mobile Augmented Reality in Unprepared Environments

  • Tobias Höllerer
  • Jason Wither
  • Stephen DiVerdi
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)


We introduce the term “Anywhere Augmentation” to refer to the idea of linking location-specific computing services with the physical world, making them readily and directly available in any situation and location. This chapter presents a novel approach to “Anywhere Augmentation” based on efficient human input for wearable computing and augmented reality (AR). Current mobile and wearable computing technologies, as found in many industrial and governmental service applications, do not routinely integrate the services they provide with the physical world. Major limitations in the computer’s general scene understanding abilities and the infeasibility of instrumenting the whole globe with a unified sensing and computing environment prevent progress in this area. Alternative approaches must be considered.

We present a mobile augmented reality system for outdoor annotation of the real world. To reduce user burden, we use openly available aerial photographs in addition to the wearable system’s usual data sources (position, orientation, camera and user input). This allows the user to accurately annotate 3D features from a single position by aligning features in both their firstperson viewpoint and in the aerial view. At the same time, aerial photographs provide a rich set of features that can be automatically extracted to create best guesses of intended annotations with minimal user input. Thus, user interaction is often as simple as casting a ray from a firstperson view, and then confirming the feature from the aerial view. We examine three types of aerial photograph features — corners, edges, and regions — that are suitable for a wide variety of useful mobile augmented reality applications. By using aerial photographs in combination with wearable augmented reality, we are able to achieve much higher accuracy 3D annotation positions from a single user location than was previously possible.


Aerial Photograph Augmented Reality Digital Surface Model Outdoor Scene Wearable Computer 
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 2007

Authors and Affiliations

  • Tobias Höllerer
    • 1
  • Jason Wither
    • 1
  • Stephen DiVerdi
    • 1
  1. 1.Four Eyes Laboratory, Department of Computer ScienceUniversity of CaliforniaSanta BarbaraUSA

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