Design of a Pupil-Matched Occlusion-Capable Optical See-Through Wearable Display

Austin Wilson, Hong Hua

Research output: Contribution to journalArticlepeer-review

Abstract

The state-of-the-art optical see-through head-mounted displays (OST-HMD) for augmented reality applications lack the ability to render correct light interaction behavior between digital and physical objects, known as mutual occlusion capability. This paper presents a novel optical architecture for enabling a compact, high performance, occlusion-capable optical see-through head-mounted display (OCOST-HMD) with correct, pupil-matched viewing perspective. The proposed design utilizes a single-layer, double-pass architecture, offering a compact OCOST-HMD solution that is capable of rendering per-pixel mutual occlusion, a correctly pupil-matched viewing between virtual and real views, and a very wide see-through field of view (FOV). Based on this architecture, we demonstrate a design embodiment and a compact prototype implementation. The prototype offers a virtual display with an FOV of 34 by 22, an angular resolution of 1.06 arc minutes per pixel, and an average image contrast greater than 40% at the Nyquist frequency of 53 cycles/mm. Further, the prototype system affords a wide see-though FOV of 90 by 50, within which about 40 diagonally is occlusion-enabled, along with an angular resolution of 1.0 arc minutes, comparable to a 20/20 vision and a dynamic range greater than 100:1. Lastly, we composed a quantitative color study that compares the effects of occlusion between a conventional HMD system and our OCOST-HMD system and the resulting response exhibited in different studies.

Original languageEnglish (US)
JournalIEEE Transactions on Visualization and Computer Graphics
DOIs
StateAccepted/In press - 2021

Keywords

  • Adaptive optics
  • Augmented reality
  • Computer architecture
  • Occlusion
  • Optical design
  • Optical imaging
  • Optical modulation
  • Optical reflection
  • Pupils
  • See-through display

ASJC Scopus subject areas

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

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