Eye-Perspective View Management for Optical See-Through Head-Mounted Displays
Abstract
Optical see-through (OST) head-mounted displays (HMDs) enable users to experience Augmented Reality (AR) support in the form of helpful real-world annotations. Unfortunately, the blend of the environment with virtual augmentations due to semitransparent OST displays often deteriorates the contrast and legibility of annotations. View management algorithms adapt the layout of annotations to improve legibility based on real-world information, typically captured by built-in HMD cameras. However, HMD camera views of the real world are distinctively different from the user's view through the OST display which decreases the final layout quality. We present a novel eye-perspective view management that utilizes synthesized high-fidelity renderings of the user’s view through the HMD to optimize annotation placement. Our method significantly improves over traditional camera-based view management in terms of annotation placement and legibility. Eye-perspective optimizations open up opportunities for further research on use cases relying on the user's true view through OST HMDs.
Information
Authors
Gerlinde Emsenhuber, Tobias Langlotz, Denis Kalkofen, Jonathan Sutton, Markus Tatzgern
Publisher
ACM CHI Conference on Human Factors in Computing Systems
Year of Publication
2023