No Jitter Please: Effects of Rotational and Positional Jitter on 3D Mid-Air Interaction

Batmaz, Anil Ufuk; Seraji, Mohammad Rajabi; Kneifel, Johanna; Stuerzlinger, Wolfgang

doi:10.1007/978-3-030-63089-8_52

Cited by 16 publications

(4 citation statements)

References 29 publications

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“…Moreover, more pronounced levels of jitter exhibit a more noticeable negative impact on user performance, particularly when dealing with smaller targets (Pavlovych and Stuerzlinger, 2009). Another observation in a separate study revealed that as jitter levels increase, users experience a significant decline in performance metrics such as time, error rate, and throughput (Batmaz et al, 2021). Additionally, a recent experiment introduced artificial jitters of 0.5°, 1°, and 1.5° in a VR system, resulting in a substantial increase in error rates with each incremental level of jitter (Moaaz et al, 2022).…”

Section: Jittermentioning

confidence: 90%

“…In summary, considering the detrimental effects of jitter on user performance in virtual reality systems highlighted by the above studies, we firmly believe that an efficient VR Typing system must possess low jitter characteristics. Given the diverse and complex causes of jitter, various research directions propose methods to reduce jitter, with the use of filters catching our attention (Batmaz et al 2021;Ribo et al 2001).…”

Section: Jittermentioning

confidence: 99%

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Development and Evaluation of Low-Jitter Hand Tracking System for Improving Typing Efficiency in Virtual Reality Workspace

Xu,

Gu,

Ota

et al. 2023

Preprint

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Virtual reality (VR) technology promises to transform immersive experiences across various applications, particularly within office environments. Despite its potential, the challenge of achieving efficient text entry in VR persists. This study addresses this obstacle by introducing a novel machine learning-based solution, namely the 2S-LSTM typing method, to enhance text entry performance in VR. The 2S-LSTM method utilizes the back-of-the-hand image, employing a two-stream Long Short-Term Memory (LSTM) network and a Kalman Filter (KF) to enhance hand position tracking accuracy and minimize jitter. Through statistical analysis of the data collected in the experiment and questionnaire results, we confirmed the effectiveness of the proposed method. In addition, we conducted an extra experiment to explore the differences in users’ typing behavior between regular typing and VR-based typing. This additional experiment provides valuable insights into how users adapt their typing behavior in different environments. These findings represent a significant step in advancing text entry within VR, setting the stage for immersive work experiences in office environments and beyond.

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Section: Jittermentioning

confidence: 90%

Section: Jittermentioning

confidence: 99%

Development and Evaluation of Low-Jitter Hand Tracking System for Improving Typing Efficiency in Virtual Reality Workspace

Xu,

Gu,

Ota

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Table 2 shows the measured metrics, each was chosen as a proxy for the points needing to be tested. The best case for positional and rotational estimations is based on hand and controller tracking as the tracking should be as accurate (Abdlkarim et al, 2023;Batmaz et al, 2021). The invasiveness of a solution is broken down into: Non-Invasive (no alterations to the object needed); Visually Invasive (visual look of the object affected); Semi-Invasive (geometry and visuals affected a small amount); Very invasive (object geometry, visuals, and weight affected); Extremely invasive (object geometry, visuals and weight massively affected).…”

Section: Metricsmentioning

confidence: 99%

6 degree of freedom positional object tracking for physical prototype digitisation

Wyrley-Birch,

Kukreja,

Gopsill

et al. 2024

Proc. Des. Soc.

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Underpinning much work on the use of Virtual Reality technologies in design prototyping, is the need to reliably track the 3D position of a physical object in real space, then allowing synchronisation with a digital counterpart. With many tracking methods requiring changes to object geometry, this work develops and benchmarks four minimally invasiveness 6 DoF tracking approaches, before discussing their use in a prototyping context. Results show that using AI and point cloud methods, accuracies of 20mm at 20Hz are achievable on low-end hardware with no alterations to the prototype needed.

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“…lighting). Providing robustness for these errors is still a hot topic of current research [70], [92]. One solution to counter the latency issues of AR systems is to use VST displays.…”

Section: Controlling and Animating Avatars In Armentioning

confidence: 99%

Being an Avatar “for Real”: A Survey on Virtual Embodiment in Augmented Reality

Genay¹,

Lécuyer

Hachet³

2022

IEEE Trans. Visual. Comput. Graphics

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Virtual self-avatars have been increasingly used in Augmented Reality (AR) where one can see virtual content embedded into physical space. However, little is known about the perception of self-avatars in such a context. The possibility that their embodiment could be achieved in a similar way as in Virtual Reality opens the door to numerous applications in education, communication, entertainment, or the medical field. This article aims to review the literature covering the embodiment of virtual self-avatars in AR. Our goal is (i) to guide readers through the different options and challenges linked to the implementation of AR embodiment systems, (ii) to provide a better understanding of AR embodiment perception by classifying the existing knowledge, and (iii) to offer insight on future research topics and trends for AR and avatar research. To do so, we introduce a taxonomy of virtual embodiment experiences by defining a "body avatarization" continuum. The presented knowledge suggests that the sense of embodiment evolves in the same way in AR as in other settings, but this possibility has yet to be fully investigated. We suggest that, whilst it is yet to be well understood, the embodiment of avatars has a promising future in AR and conclude by discussing possible directions for research.

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No Jitter Please: Effects of Rotational and Positional Jitter on 3D Mid-Air Interaction

Cited by 16 publications

References 29 publications

Development and Evaluation of Low-Jitter Hand Tracking System for Improving Typing Efficiency in Virtual Reality Workspace

Development and Evaluation of Low-Jitter Hand Tracking System for Improving Typing Efficiency in Virtual Reality Workspace

6 degree of freedom positional object tracking for physical prototype digitisation

Being an Avatar “for Real”: A Survey on Virtual Embodiment in Augmented Reality

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