Learning Effect of Lay People in Gesture-Based Locomotion in Virtual
Reality
- URL: http://arxiv.org/abs/2206.08076v1
- Date: Thu, 16 Jun 2022 10:44:16 GMT
- Title: Learning Effect of Lay People in Gesture-Based Locomotion in Virtual
Reality
- Authors: Alexander Sch\"afer, Gerd Reis, Didier Stricker
- Abstract summary: Some of the most promising methods are gesture-based and do not require additional handheld hardware.
Recent work focused mostly on user preference and performance of the different locomotion techniques.
This work is investigated whether and how quickly users can adapt to a hand gesture-based locomotion system in VR.
- Score: 81.5101473684021
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Locomotion in Virtual Reality (VR) is an important part of VR applications.
Many scientists are enriching the community with different variations that
enable locomotion in VR. Some of the most promising methods are gesture-based
and do not require additional handheld hardware. Recent work focused mostly on
user preference and performance of the different locomotion techniques. This
ignores the learning effect that users go through while new methods are being
explored. In this work, it is investigated whether and how quickly users can
adapt to a hand gesture-based locomotion system in VR. Four different
locomotion techniques are implemented and tested by participants. The goal of
this paper is twofold: First, it aims to encourage researchers to consider the
learning effect in their studies. Second, this study aims to provide insight
into the learning effect of users in gesture-based systems.
Related papers
- Development of a Virtual Reality Application for Oculomotor Examination Education Based on Student-Centered Pedagogy [3.876880241607719]
This work-in-progress paper discusses the use of student-centered pedagogy to teach clinical oculomotor examination via Virtual Reality (VR)
Traditional methods, such as PowerPoint slides and lab activities, are often insufficient for providing hands-on experience due to the high cost of clinical equipment.
A VR-based application was developed using Unity and the HTC Vive Pro headset, offering a cost-effective solution for practical learning.
arXiv Detail & Related papers (2024-05-26T00:53:19Z) - Tremor Reduction for Accessible Ray Based Interaction in VR Applications [0.0]
Many traditional 2D interface interaction methods have been directly converted to work in a VR space with little alteration to the input mechanism.
In this paper we propose the use of a low pass filter, to normalize user input noise, alleviating fine motor requirements during ray-based interaction.
arXiv Detail & Related papers (2024-05-12T17:07:16Z) - Learning High-Quality Navigation and Zooming on Omnidirectional Images in Virtual Reality [37.564863636844905]
We present a novel system, called OmniVR, designed to enhance visual clarity during VR navigation.
Our system enables users to effortlessly locate and zoom in on the objects of interest in VR.
arXiv Detail & Related papers (2024-05-01T07:08:24Z) - Universal Humanoid Motion Representations for Physics-Based Control [71.46142106079292]
We present a universal motion representation that encompasses a comprehensive range of motor skills for physics-based humanoid control.
We first learn a motion imitator that can imitate all of human motion from a large, unstructured motion dataset.
We then create our motion representation by distilling skills directly from the imitator.
arXiv Detail & Related papers (2023-10-06T20:48:43Z) - Moving Avatars and Agents in Social Extended Reality Environments [16.094148092964264]
We introduce a Smart Avatar system that delivers continuous full-body human representations for noncontinuous locomotion in VR spaces.
We also introduce the concept of Stuttered Locomotion, which can be applied to any continuous locomotion method.
We will discuss the potential of Smart Avatars and Stuttered Locomotion for shared VR experiences.
arXiv Detail & Related papers (2023-06-26T07:51:17Z) - Force-Aware Interface via Electromyography for Natural VR/AR Interaction [69.1332992637271]
We design a learning-based neural interface for natural and intuitive force inputs in VR/AR.
We show that our interface can decode finger-wise forces in real-time with 3.3% mean error, and generalize to new users with little calibration.
We envision our findings to push forward research towards more realistic physicality in future VR/AR.
arXiv Detail & Related papers (2022-10-03T20:51:25Z) - A Systematic Review on Interactive Virtual Reality Laboratory [1.3999481573773072]
This study aims to comprehend the work done in quality education from a distance using VR.
Adopting virtual reality in education can help students learn more effectively.
This highlights the importance of a significant expansion of VR use in learning.
arXiv Detail & Related papers (2022-03-26T07:16:01Z) - Wireless Edge-Empowered Metaverse: A Learning-Based Incentive Mechanism
for Virtual Reality [102.4151387131726]
We propose a learning-based Incentive Mechanism framework for VR services in the Metaverse.
First, we propose the quality of perception as the metric for VR users in the virtual world.
Second, for quick trading of VR services between VR users (i.e., buyers) and VR SPs (i.e., sellers), we design a double Dutch auction mechanism.
Third, for auction communication reduction, we design a deep reinforcement learning-based auctioneer to accelerate this auction process.
arXiv Detail & Related papers (2021-11-07T13:02:52Z) - Learning Perceptual Locomotion on Uneven Terrains using Sparse Visual
Observations [75.60524561611008]
This work aims to exploit the use of sparse visual observations to achieve perceptual locomotion over a range of commonly seen bumps, ramps, and stairs in human-centred environments.
We first formulate the selection of minimal visual input that can represent the uneven surfaces of interest, and propose a learning framework that integrates such exteroceptive and proprioceptive data.
We validate the learned policy in tasks that require omnidirectional walking over flat ground and forward locomotion over terrains with obstacles, showing a high success rate.
arXiv Detail & Related papers (2021-09-28T20:25:10Z) - Learning Agile Robotic Locomotion Skills by Imitating Animals [72.36395376558984]
Reproducing the diverse and agile locomotion skills of animals has been a longstanding challenge in robotics.
We present an imitation learning system that enables legged robots to learn agile locomotion skills by imitating real-world animals.
arXiv Detail & Related papers (2020-04-02T02:56:16Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.