Breathing Life into static Visualizations using AR

Theoretical (Analytical):

Practical (Implementation):

Literature Work:


Overview

During presentations or business meeting, it is often not feasible to show interactive visualizations of data. Instead, static images of these visualizations are shown. Using Augmented Reality technology, an interactive copy of the visualization could be created and presented to the user. The user is then able to interact with this copy in order to analyze the data.
The project will develop a Unity framework for the inspection of static visualizations in AR (HTC Vive / Microsoft HoloLens). The static visualization (print-out, draft, etc.) should be recognized with image processing (edge detection etc.) and overlaid with a digital copy with which the observer can interact with. 

Problem Statement

A major drawback of static visualizations is their incapability to adapt to changes in the data or visualization parameters. AR technology could overcome this problem by creating a dynamic digital clone of the static visualization. 

Tasks

  • Get familiar with Unity and the technical requirements for AR/see-through (especially if using HTC Vive). 
  • Get familiar with image recognition and detection algorithms.
  • Create a framework that is capable of digitalizing a static visualization and extend it by basic interaction functionalities

    Requirements

    • Advanced skills in image processing, AR/VR applications and Unity
    • Advanced programming skills in Java or C#
    • Useful: Git

      Scope/Duration/Start

      • Scope: Bachelor/Master
      • 6 Month Project
      • 3/6 Month Thesis

        Contact

          References

          • Kim, T., Saket, B., Endert, A., & MacIntyre, B. (2017). VisAR: Bringing Interactivity to Static Data Visualizations through Augmented Reality. arXiv preprint arXiv:1708.01377.
          • Saenz, M., Baigelenov, A., Hung, Y. H., & Parsons, P. Reexamining the cognitive utility of 3D visualizations using augmented reality holograms. IEEE VIS 2017.