PEA-PODs: Perceptual Evaluation of Algorithms for Power Optimization in XR Displays

Kenneth Chen, Thomas Wan, Nathan Matsuda, Ajit Ninan, Alexandre Chapiro, Qi Sun

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Display power consumption is an emerging concern for untethered devices. This goes double for augmented and virtual extended reality (XR) displays, which target high refresh rates and high resolutions while conforming to an ergonomically light form factor. A number of image mapping techniques have been proposed to extend battery usage. However, there is currently no comprehensive quantitative understanding of how the power savings provided by these methods compare to their impact on visual quality. We set out to answer this question. To this end, we present a perceptual evaluation of algorithms (PEA) for power optimization in XR displays (PODs). Consolidating a portfolio of six power-saving display mapping approaches, we begin by performing a large-scale perceptual study to understand the impact of each method on perceived quality in the wild. This results in a unified quality score for each technique, scaled in just-objectionable-difference (JOD) units. In parallel, each technique is analyzed using hardware-accurate power models. The resulting JOD-to-Milliwatt transfer function provides a first-of-its-kind look into tradeoffs offered by display mapping techniques, and can be directly employed to make architectural decisions for power budgets on XR displays.

    Original languageEnglish (US)
    Article number67
    JournalACM Transactions on Graphics
    Volume43
    Issue number4
    DOIs
    StatePublished - Jul 19 2024

    Keywords

    • display power
    • visual perception
    • VR/AR

    ASJC Scopus subject areas

    • Computer Graphics and Computer-Aided Design

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