Context-Responsive Labeling in Augmented Reality

Information

• Publication Type: Master Thesis
• Workgroup(s)/Project(s):
  • Visualization Group
• Date: November 2020
• Date (Start): 12. February 2020
• Date (End): 18. November 2020
• Second Supervisor: Hsiang-Yun Wu
• Diploma Examination: 18. November 2020
• Open Access: yes
• First Supervisor: Eduard Gröller

Abstract

Route planning is a common task that often requires additional information on Points-of-Interest (POIs). Augmented Reality (AR) enables mobile users to explore text labels and provides a composite view associated with additional information in a real-world environment. Displaying all labels for Points-of-Interest on a mobile device will lead to unwanted overlaps, and thus a context-responsive strategy to properly arrange labels is expected. This framework should consider removing overlaps, the correct Level-of-Detail to be presented, and also label coherence. This is necessary as the viewing angle in an AR system may change frequently due to users’ behaviors. The consistency of labels plays an essential role in retaining user experience and knowledge, as well as avoiding motion sickness. In this thesis, we aim to develop an approach that systematically manages label visibility and Levels-of-Detail, as well as eliminates unexpected incoherent label movement. To achieve this, we introduce three label management strategies, including (1) Occlusion Management, (2) Level-of-Detail Management, and (3) Coherence Management. A greedy approach is developed for fast occlusion handling. A Level-of-Detail scheme is adopted to arrange various types of labels in AR. A 3D scene manipulation is built to simultaneously suppress the incoherent behaviors induced by the changes of viewing angles. Finally, we present our approach’s feasibility and applicability by demonstrating one synthetic and two real-world scenarios, followed by a qualitative user study.

Additional Files and Images

Weblinks

• Entry in reposiTUm (TU Wien Publication Database)

BibTeX

@mastersthesis{Koeppel2020,
  title =      "Context-Responsive Labeling in Augmented Reality",
  author =     "Thomas K\"{o}ppel",
  year =       "2020",
  abstract =   "Route planning is a common task that often requires
               additional information on Points-of-Interest (POIs).
               Augmented Reality (AR) enables mobile users to explore text
               labels and provides a composite view associated with
               additional information in a real-world environment.
               Displaying all labels for Points-of-Interest on a mobile
               device will lead to unwanted overlaps, and thus a
               context-responsive strategy to properly arrange labels is
               expected. This framework should consider removing overlaps,
               the correct Level-of-Detail to be presented, and also label
               coherence. This is necessary as the viewing angle in an AR
               system may change frequently due to users’ behaviors. The
               consistency of labels plays an essential role in retaining
               user experience and knowledge, as well as avoiding motion
               sickness. In this thesis, we aim to develop an approach that
               systematically manages label visibility and
               Levels-of-Detail, as well as eliminates unexpected
               incoherent label movement. To achieve this, we introduce
               three label management strategies, including (1) Occlusion
               Management, (2) Level-of-Detail Management, and (3)
               Coherence Management. A greedy approach is developed for
               fast occlusion handling. A Level-of-Detail scheme is adopted
               to arrange various types of labels in AR. A 3D scene
               manipulation is built to simultaneously suppress the
               incoherent behaviors induced by the changes of viewing
               angles. Finally, we present our approach’s feasibility and
               applicability by demonstrating one synthetic and two
               real-world scenarios, followed by a qualitative user study.",
  month =      nov,
  address =    "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria",
  school =     "Research Unit of Computer Graphics, Institute of Visual
               Computing and Human-Centered Technology, Faculty of
               Informatics, TU Wien",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2020/Koeppel2020/",
}