The influence of label design on search performance and noticeability in wide field of view augmented reality displays

Ernst Kruijff, Jason Orlosky, Naohiro Kishishita, Christina Trepkowski, Kiyoshi Kiyokawa

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

In Augmented Reality (AR), search performance for outdoor tasks is an important metric for evaluating the success of a large number of AR applications. Users must be able to find content quickly, labels and indicators must not be invasive but still clearly noticeable, and the user interface should maximize search performance in a variety of conditions. To address these issues, we have set up a series of experiments to test the influence of virtual characteristics such as color, size, and leader lines on the performance of search tasks and noticeability in both real and simulated environments. We evaluate two primary areas, including 1) the effects of peripheral field of view (FOV) limitations and labeling techniques on target acquisition during outdoor mobile search, and 2) the influence of local characteristics such as color, size, and motion on text labels over dynamic backgrounds. The first experiment showed that limited FOV will severely limit search performance, but that appropriate placement of labels and leaders within the periphery can alleviate this problem without interfering with walking or decreasing user comfort. In the second experiment, we found that different types of motion are more noticeable in optical versus video see-through displays, but that blue coloration is most noticeable in both. Results can aid in designing more effective view management techniques, especially for wider field of view displays.

Original languageEnglish (US)
Article number8409318
Pages (from-to)2821-2837
Number of pages17
JournalIEEE Transactions on Visualization and Computer Graphics
Volume25
Issue number9
DOIs
StatePublished - Sep 1 2019
Externally publishedYes

Keywords

  • Augmented reality
  • head mounted display
  • perception
  • peripheral vision
  • visualization

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design

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