Reducing Latency by Eliminating Synchrony

Yun, Min Hong; He, Songtao; Lin, Zhouchen

doi:10.1145/3038912.3052557

Cited by 4 publications

(6 citation statements)

References 20 publications

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“…While our digital ink's latency is perceptible, the subjects of the user study did not mention it explicitly. To reduce the overall latency of commercially available state-of-the-art styluses, touch prediction algorithms are applied, which for example, reduces the latency of the Apple Pencil on an Apple iPad Pro to 42.9 ms (Yun et al, 2017). These findings are similar with evaluations by Helps and Helps (2016) measuring an average latency of 47.88 ms (SD 9.04 ms) (iPad Pro using the native application Apple Notes).…”

Section: Discussionsupporting

confidence: 63%

“…For professional sketching applications (e.g., Autodesk Sketch) the average latency was even higher with 82.85 ms (SD 10.1 ms). As non-native applications do not have access to these touch predictions and especially web browsers induce additional latency due to script executions or asynchronous frame rates (Yun et al, 2017) using HTML5-Canvases implemented in commercially available whiteboards, commercial styluses also produce a noticeable delay of the digital ink. Compared to previous measurements in (Helps and Helps, 2016;Yun et al, 2017), our results for the stylus movement (M 42.57 ms) and digital ink measurement (M 79.40 ms) are similar.…”

Section: Discussionmentioning

confidence: 99%

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Off-The-Shelf Stylus: Using XR Devices for Handwriting and Sketching on Physically Aligned Virtual Surfaces

Kern

Kullmann

Ganal

et al. 2021

Front. Virtual Real.

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This article introduces the Off-The-Shelf Stylus (OTSS), a framework for 2D interaction (in 3D) as well as for handwriting and sketching with digital pen, ink, and paper on physically aligned virtual surfaces in Virtual, Augmented, and Mixed Reality (VR, AR, MR: XR for short). OTSS supports self-made XR styluses based on consumer-grade six-degrees-of-freedom XR controllers and commercially available styluses. The framework provides separate modules for three basic but vital features: 1) The stylus module provides stylus construction and calibration features. 2) The surface module provides surface calibration and visual feedback features for virtual-physical 2D surface alignment using our so-called 3ViSuAl procedure, and surface interaction features. 3) The evaluation suite provides a comprehensive test bed combining technical measurements for precision, accuracy, and latency with extensive usability evaluations including handwriting and sketching tasks based on established visuomotor, graphomotor, and handwriting research. The framework’s development is accompanied by an extensive open source reference implementation targeting the Unity game engine using an Oculus Rift S headset and Oculus Touch controllers. The development compares three low-cost and low-tech options to equip controllers with a tip and includes a web browser-based surface providing support for interacting, handwriting, and sketching. The evaluation of the reference implementation based on the OTSS framework identified an average stylus precision of 0.98 mm (SD = 0.54 mm) and an average surface accuracy of 0.60 mm (SD = 0.32 mm) in a seated VR environment. The time for displaying the stylus movement as digital ink on the web browser surface in VR was 79.40 ms on average (SD = 23.26 ms), including the physical controller’s motion-to-photon latency visualized by its virtual representation (M = 42.57 ms, SD = 15.70 ms). The usability evaluation (N = 10) revealed a low task load, high usability, and high user experience. Participants successfully reproduced given shapes and created legible handwriting, indicating that the OTSS and it’s reference implementation is ready for everyday use. We provide source code access to our implementation, including stylus and surface calibration and surface interaction features, making it easy to reuse, extend, adapt and/or replicate previous results (https://go.uniwue.de/hci-otss).

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Section: Discussionsupporting

confidence: 63%

Section: Discussionmentioning

confidence: 99%

Off-The-Shelf Stylus: Using XR Devices for Handwriting and Sketching on Physically Aligned Virtual Surfaces

Kern

Kullmann

Ganal

et al. 2021

Front. Virtual Real.

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“…Depending on the devices and applications, the amount of end-to-end latency ranges from 21 to 277 ms, composed of input latencies of 2-30 ms and output latencies between 19 ms and 247 ms [10]. Latencies in touchscreen devices such as smartphones or tablet PCs range from 50 to 200 ms [15,21,52].…”

Section: Related Work Latency and Its Measurementmentioning

confidence: 99%

“…Reducing the amount of end-to-end latency is the most direct way to decrease the effect of latency [44]. Researchers have been improving hardware and software to minimize the total latency, by such means as considering the best locations for game servers [3] and developing software that eliminates delays from synchrony [52]. The main goal with these has been to reduce latency to an imperceivable level [34].…”

Section: Reducing Effects Of Latencymentioning

confidence: 99%

“…Latency, which is not intentionally created or considered, has always existed in typical computing environments. The amount of end-to-end latency varies from computing platforms and their conditions, ranging from 21-277 ms for desktop to over 50 ms for touchscreen environments [10,34,52]. Latency is often inevitable, not controllable, and vary among devices.…”

Section: Introductionmentioning

confidence: 99%

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Geometrically Compensating Effect of End-to-End Latency in Moving-Target Selection Games

Lee

Kim

Lee

2019

Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems

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Effects of unintended latency on gamer performance have been reported. End-to-end latency can be corrected by postinput manipulation of activation times, but this gives the player unnatural gameplay experience. For moving-target selection games such as Flappy Bird, the paper presents a predictive model of latency on error rate and a novel compensation method for the latency effects by adjusting the game's geometry design-e.g., by modifying the size of the selection region. Without manipulation of the game clock, this can keep the user's error rate constant even if the endto-end latency of the system changes. The approach extends the current model of moving-target selection with two additional assumptions about the effects of latency: (1) latency reduces players' cue-viewing time and (2) pushes the mean of the input distribution backward. The model and method proposed have been validated through precise experiments.

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