Locomotion vault: the extra mile in analyzing VR locomotion techniques

Max Di Luca; Hasti Seifi; Simon Egan; Mar Gonzalez-Franco

doi:10.1145/3411764.3445319

Locomotion vault: the extra mile in analyzing VR locomotion techniques

Max Di Luca, Hasti Seifi, Simon Egan, Mar Gonzalez-Franco

Psychology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

550 Downloads (Pure)

Abstract

Numerous techniques have been proposed for locomotion in virtual reality (VR). Several taxonomies consider a large number of attributes (e.g., hardware, accessibility) to characterize these techniques. However, finding the appropriate locomotion technique (LT) and identifying gaps for future designs in the high-dimensional space of attributes can be quite challenging. To aid analysis and innovation, we devised Locomotion Vault (https://locomotionvault.github.io/), a database and visualization of over 100 LTs from academia and industry. We propose similarity between LTs as a metric to aid navigation and visualization. We show that similarity based on attribute values correlates with expert similarity assessments (a method that does not scale). Our analysis also highlights an inherent trade-off between simulation sickness and accessibility across LTs. As such, Locomotion Vault shows to be a tool that unifies information on LTs and enables their standardization and large-scale comparison to help understand the space of possibilities in VR locomotion.

Original language	English
Title of host publication	CHI '21
Subtitle of host publication	Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Publisher	Association for Computing Machinery (ACM)
Number of pages	10
ISBN (Print)	9781450380966
DOIs	https://doi.org/10.1145/3411764.3445319
Publication status	Published - 6 May 2021
Event	CHI '21: CHI Conference on Human Factors in Computing Systems: Making Waves, Combining Strengths - Virtual, Virtual, Online, Japan Duration: 8 May 2021 → 13 May 2021 https://chi2021.acm.org/

Publication series

Name	CHI: Conference on Human Factors in Computing Systems

Conference

Conference	CHI '21: CHI Conference on Human Factors in Computing Systems
Abbreviated title	CHI 2021
Country/Territory	Japan
City	Virtual, Online
Period	8/05/21 → 13/05/21
Internet address	https://chi2021.acm.org/

Keywords

Database
Locomotion method
Locomotion technique
Movement
Navigation
Traveling
Visualization
Vr

ASJC Scopus subject areas

Human-Computer Interaction
Computer Graphics and Computer-Aided Design
Software

Access to Document

10.1145/3411764.3445319

DiLucaM2021LocomotionAccepted author manuscript, 6.71 MBLicence: None: All rights reserved

Cite this

Di Luca, M., Seifi, H., Egan, S., & Gonzalez-Franco, M. (2021). Locomotion vault: the extra mile in analyzing VR locomotion techniques. In CHI '21: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems Article 128 (CHI: Conference on Human Factors in Computing Systems). Association for Computing Machinery (ACM). https://doi.org/10.1145/3411764.3445319

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title = "Locomotion vault: the extra mile in analyzing VR locomotion techniques",

abstract = "Numerous techniques have been proposed for locomotion in virtual reality (VR). Several taxonomies consider a large number of attributes (e.g., hardware, accessibility) to characterize these techniques. However, finding the appropriate locomotion technique (LT) and identifying gaps for future designs in the high-dimensional space of attributes can be quite challenging. To aid analysis and innovation, we devised Locomotion Vault (https://locomotionvault.github.io/), a database and visualization of over 100 LTs from academia and industry. We propose similarity between LTs as a metric to aid navigation and visualization. We show that similarity based on attribute values correlates with expert similarity assessments (a method that does not scale). Our analysis also highlights an inherent trade-off between simulation sickness and accessibility across LTs. As such, Locomotion Vault shows to be a tool that unifies information on LTs and enables their standardization and large-scale comparison to help understand the space of possibilities in VR locomotion.",

keywords = "Database, Locomotion method, Locomotion technique, Movement, Navigation, Traveling, Visualization, Vr",

author = "{Di Luca}, Max and Hasti Seifi and Simon Egan and Mar Gonzalez-Franco",

year = "2021",

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doi = "10.1145/3411764.3445319",

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series = "CHI: Conference on Human Factors in Computing Systems",

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Di Luca, M, Seifi, H, Egan, S & Gonzalez-Franco, M 2021, Locomotion vault: the extra mile in analyzing VR locomotion techniques. in CHI '21: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems., 128, CHI: Conference on Human Factors in Computing Systems, Association for Computing Machinery (ACM), CHI '21: CHI Conference on Human Factors in Computing Systems, Virtual, Online, Japan, 8/05/21. https://doi.org/10.1145/3411764.3445319

Locomotion vault: the extra mile in analyzing VR locomotion techniques. / Di Luca, Max; Seifi, Hasti; Egan, Simon et al.
CHI '21: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery (ACM), 2021. 128 (CHI: Conference on Human Factors in Computing Systems).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Locomotion vault

T2 - CHI '21: CHI Conference on Human Factors in Computing Systems

AU - Di Luca, Max

AU - Seifi, Hasti

AU - Egan, Simon

AU - Gonzalez-Franco, Mar

PY - 2021/5/6

Y1 - 2021/5/6

N2 - Numerous techniques have been proposed for locomotion in virtual reality (VR). Several taxonomies consider a large number of attributes (e.g., hardware, accessibility) to characterize these techniques. However, finding the appropriate locomotion technique (LT) and identifying gaps for future designs in the high-dimensional space of attributes can be quite challenging. To aid analysis and innovation, we devised Locomotion Vault (https://locomotionvault.github.io/), a database and visualization of over 100 LTs from academia and industry. We propose similarity between LTs as a metric to aid navigation and visualization. We show that similarity based on attribute values correlates with expert similarity assessments (a method that does not scale). Our analysis also highlights an inherent trade-off between simulation sickness and accessibility across LTs. As such, Locomotion Vault shows to be a tool that unifies information on LTs and enables their standardization and large-scale comparison to help understand the space of possibilities in VR locomotion.

AB - Numerous techniques have been proposed for locomotion in virtual reality (VR). Several taxonomies consider a large number of attributes (e.g., hardware, accessibility) to characterize these techniques. However, finding the appropriate locomotion technique (LT) and identifying gaps for future designs in the high-dimensional space of attributes can be quite challenging. To aid analysis and innovation, we devised Locomotion Vault (https://locomotionvault.github.io/), a database and visualization of over 100 LTs from academia and industry. We propose similarity between LTs as a metric to aid navigation and visualization. We show that similarity based on attribute values correlates with expert similarity assessments (a method that does not scale). Our analysis also highlights an inherent trade-off between simulation sickness and accessibility across LTs. As such, Locomotion Vault shows to be a tool that unifies information on LTs and enables their standardization and large-scale comparison to help understand the space of possibilities in VR locomotion.

KW - Database

KW - Locomotion method

KW - Locomotion technique

KW - Movement

KW - Navigation

KW - Traveling

KW - Visualization

KW - Vr

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M3 - Conference contribution

SN - 9781450380966

T3 - CHI: Conference on Human Factors in Computing Systems

BT - CHI '21

PB - Association for Computing Machinery (ACM)

Y2 - 8 May 2021 through 13 May 2021

ER -

Locomotion vault: the extra mile in analyzing VR locomotion techniques

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this