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MazeRunVR: An Open Benchmark for VR Locomotion Performance, Preference and Sickness in the Wild

Ragozin, Kirill ; Kunze, Kai ; Marky, Karola ; Pai, Yun Suen (2020):
MazeRunVR: An Open Benchmark for VR Locomotion Performance, Preference and Sickness in the Wild.
CHI EA ’20: Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems, ISBN 9781450368193,
DOI: 10.1145/3334480.3383035,
[Conference or Workshop Item]

Abstract

Locomotion in virtual reality (VR) is one of the biggest problems for large scale adoption of VR applications. Yet, to our knowledge, there are few studies conducted in-the-wild to understand performance metrics and general user preference for different mechanics. In this paper, we present the first steps towards an open framework to create a VR locomotion benchmark. As a viability study, we investigate how well the users move in VR when using three different locomotion mechanics. It was played in over 124 sessions across 10 countries in a period of three weeks. The included prototype locomotion mechanics are arm swing,walk-in-place and trackpad movement. We found that over-all, users performed significantly faster using arm swing and trackpad when compared to walk-in-place. For subjective preference, arm swing was significantly more preferred over the other two methods. Finally for induced sickness, walk-in-place was the overall most sickness-inducing locomotion method.

Item Type: Conference or Workshop Item
Erschienen: 2020
Creators: Ragozin, Kirill ; Kunze, Kai ; Marky, Karola ; Pai, Yun Suen
Title: MazeRunVR: An Open Benchmark for VR Locomotion Performance, Preference and Sickness in the Wild
Language: English
Abstract:

Locomotion in virtual reality (VR) is one of the biggest problems for large scale adoption of VR applications. Yet, to our knowledge, there are few studies conducted in-the-wild to understand performance metrics and general user preference for different mechanics. In this paper, we present the first steps towards an open framework to create a VR locomotion benchmark. As a viability study, we investigate how well the users move in VR when using three different locomotion mechanics. It was played in over 124 sessions across 10 countries in a period of three weeks. The included prototype locomotion mechanics are arm swing,walk-in-place and trackpad movement. We found that over-all, users performed significantly faster using arm swing and trackpad when compared to walk-in-place. For subjective preference, arm swing was significantly more preferred over the other two methods. Finally for induced sickness, walk-in-place was the overall most sickness-inducing locomotion method.

ISBN: 9781450368193
Uncontrolled Keywords: framework, virtual reality, locomotion, in the wild
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Telecooperation
Event Title: CHI EA ’20: Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems
Date Deposited: 26 Jun 2020 07:57
DOI: 10.1145/3334480.3383035
Official URL: https://doi.org/10.1145/3334480.3383035
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