Stimulating the Human Visual System Beyond Real World Performance in Future Augmented Reality Displays

Abstract

New augmented-reality near-eye displays provide capabilities for enriching real-world visual experiences with digital content. Most current research focuses on improving both hardware and software to provide digital content that seamlessly blends with the real world. This is believed to not only contribute to the visual experience but also increase human task performance. In this work, we take a step further and ask the question of whether the capabilities of current and future display designs combined with efficient perceptioninspired content optimizations can be used to improve human task performance beyond the human capabilities in the natural world. Based on an in-depth analysis of previous literature, we hypothesize here that such enhancements can be achieved when the human visual system is provided with content that optimizes the oculomotor responses. To further investigate possible gains, we present a series of perceptual experiments that built upon this idea. More specifically, we focus on speeding up accommodation response, which significantly contributes to the eye-adaptation when a new stimulus is shown. Through our experiments, we demonstrate that such speedups can be achieved, and more importantly, they can lead to significant improvements in human task performance. While not all of our results give definite answers, we believe that they reveal plentiful opportunities for further enhancing the human experience and task performance when using new augmented-reality displays.

User's image perception improved strategy and application of augmented reality systems in smart medical care: A review

“…AR systems are usually classified into three types based on their display principles: The systems that rely entirely on optical elements and can directly observe real scenes through optical elements are classified as Optical‐based AR systems; the systems that replace the real environment captured by the human eye with a real environment captured by a camera and processed by a computer are classified as Video‐based AR systems; the systems that project virtual images directly onto real‐world surfaces via projectors are classified as Projection‐based AR systems. After practical clinical application, researchers found that different types of AR systems have different effects on physicians' image perception 44–47 …”

“…After practical clinical application, researchers found that different types of AR systems have different effects on physicians' image perception. [44][45][46][47] This study reviews the present state of image perception optimisation for various display kinds of AR systems and their applications in the field of smart medical care. The second part of the article uses Citespace to examine the current literature in order to identify the hot areas and major directions of current research on AR systems in the field of smart medical data visualisation.…”

Playing with Data: An Augmented Reality Approach to Interact with Visualizations of Industrial Process Tomography

“…With the ability of displaying manifold data in a more perceivable and interactive way Heemsbergen et al [2021], Dubois et al [2001], applying AR to generate interactive visualizations for user-oriented tasks is often the preferred choice, and not only for industrial applications Masood and Egger [2020], Fite-Georgel [2011], Ong and Nee [2013], Mourtzis et al [2020], Alves et al [2022]. More specifically, it has been proven that OST AR can insert the virtual information into the physical environment with visual enhancement for human observers to control, thus improving the performance of information-dense domain tasks and further adding to its appeal to industrial practitioners Dunn et al [2020], Henderson and Feiner [2011].…”

Image Features Influence Reaction Time: A Learned Probabilistic Perceptual Model for Saccade Latency

“…Measuring, modeling, and predicting how humans perceive and act on displayed visual content are important tasks in computer graphics, with applications in cinematic, real-time rendering, virtual/augmented reality (VR/AR), display optimization, esports, video compression/streaming, and visual design [Dunn et al 2020;Mantiuk et al 2004;Patney et al 2016;Serrano et al 2017;Sitzmann et al 2018]. Perceptual image quality metrics predict the likelihood of visibility of image artifacts that result from creative and technical design, or are a side-effect of rendering, processing, or transmission.…”