Presentation + Paper
21 June 2019 Evaluation of augmented reality (AR) displays performance based on human visual perception
Author Affiliations +
Abstract
Conventional display metrics1 are currently used to evaluate the performance of augmented reality (AR) displays: the maximum luminance it can reach, the image uniformity, the contrast ratio and others. However, these metrics initially defined for non-transmissive displays, do not consider the impact of the see-through environment2 as it exists in AR applications. These measurements (usually obtained in a dark laboratory) are used to quantify the performance of AR display devices, but do not necessary relates to the perceived quality of images rendered by such devices, due to the non-linearity of human perception. Upon this, the projected image (Fig. 1) is an overlay upon the see-through environment. The intensity balance between these two “layers” becomes critical as the perceived scene (Fig. 2) is resulting from color mixing. Here, we want to highlight the fact that the brightness (perceived intensity) and color uniformity2 of the projected image becomes less important whereas the contrast ratio between the image and the environment becomes very critical. Other metrics are also less significant once the outside scene is added such as pixel sharpness2 (MTF) and the generated halo effects. These metrics are still important to evaluate the display performance for comparison purpose, but higher thresholds should be permitted for an AR display. The performance requirements must be adjusted in accordance to the AR application itself and not as it is done for conventional displays.
Conference Presentation
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sébastien de Cunsel "Evaluation of augmented reality (AR) displays performance based on human visual perception", Proc. SPIE 11062, Digital Optical Technologies 2019, 110620V (21 June 2019); https://doi.org/10.1117/12.2527613
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Augmented reality

Eye

Modulation transfer functions

Image transmission

LCDs

Autoregressive models

Image quality

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