Measuring System Visual Latency through Cognitive Latency on Video See-Through AR devices

Abstract

Figure 1: Latency was tested both through a hardware instrumentation-based measurement (bottom left) and the new cognitive latency technique (bottom right) on four different devices. The first device, Prism, was an ad-hoc system that attached a pair of colour cameras to an Acer Windows Mixed Reality device (1 top left). This system aimed at providing a top end video see-through quality. We also tested Oculus Quest (2), Oculus Rift S (3) and the Valve Index (4). On the Bottom Left, hardware instrumentation-based measurement setup. Cameras (A and B) are synchronized to capture at the exact same time by the board (2). While (1) is a clock running at sub-millisecond accuracy. The clock for camera (B) is seen by the HMD (3), which displays the video see-through. The scene was kept well illuminated to reduce automatic exposure time problems of the HMD cameras. On the Bottom Right, a participant performing the rapid decision making task while wearing a see-through VR headset.

Identifying Causes of and Solutions for Cybersickness in Immersive Technology: Reformulation of a Research and Development Agenda

“…The 1998 R&D agenda also called for reduced latencies (but visual latency issues persist today; see Gruen et al, 2020), establishment of cross-platform software with portability (which Unity, Unreal Engine, and other development platforms now support), improved tracking technology (now often seamlessly integrated into the VR/AR headset technology itself), and creation of better haptic interfaces (tactile and force feedback is still rudimentary, but hand tracking and gesture recognition have been integrated into some VR/AR headsets). While modern multicore processors have made it possible to render complex auditory environments over headphones integrated into headsets, other senses have yet to be incorporated adequately (including, vestibular, chemical, or non-haptic somatosensory cues such as body cutaneous and kinesthetic stimuli).…”

Surface EMG vs. High-Density EMG: Tradeoff Between Performance and Usability for Head Orientation Prediction in VR Application

“…The authors' hardwareinstrumentation-based measurements showed that the Prism device had the lowest latency, with 54 ± 1.9 ms. Meanwhile, the Valve Index had the largest latency, with 94 ± 2.1 ms [8]. Furthermore, a study from Staufert et al measured latency on an HTC Vive, and the result was 54.51 ± 8.6 ms [6], while the older version of Oculus VR, Oculus DK2, showed latency as high as 84 ± 6.3 ms, as measured by Feldstein et al [9].…”

“…Even though this study predicted 6DoF motion among VR users, the data collected from the sample did not explore the worst-case scenarios for when the user performs abrupt movements while playing VR games, focusing instead on scenery-based VR apps. Another limitation in this study was their use of 60 window time data (666 ms) to predict only 11 ms in the future, which is not practical since recent VR-HMDs still have latency between 43 and 85 ms [5][6][7][8][9].…”

“…Moreover, recent literature from 2019-2020 showed that current VR-HMD still possesses an MTP latency varying between 43 and 85 ms [5][6][7][8][9]. Using an Acer device, R. Gruen et al (2020) tested the latency on four different VR devices: Oculus Rift S, Valve Index, Oculus Quest, and Prim. The first of these devices was a standalone VR headset, while the others were PC-based VR headsets [8].…”

“…Using an Acer device, R. Gruen et al (2020) tested the latency on four different VR devices: Oculus Rift S, Valve Index, Oculus Quest, and Prim. The first of these devices was a standalone VR headset, while the others were PC-based VR headsets [8]. The authors' hardwareinstrumentation-based measurements showed that the Prism device had the lowest latency, with 54 ± 1.9 ms.…”