short-paper

Perceived Realism of Pedestrian Crowds Trajectories in VR

Authors:

Daniele Giunchi,

Panayiotis Charalambous,

Fotis Liarokapis,

Alastair Shipman,

Thomas HeinisAuthors Info & Claims

VRST '21: Proceedings of the 27th ACM Symposium on Virtual Reality Software and Technology

Article No.: 38, Pages 1 - 5

https://doi.org/10.1145/3489849.3489860

Published: 08 December 2021 Publication History

Abstract

Crowd simulation algorithms play an essential role in populating Virtual Reality (VR) environments with multiple autonomous humanoid agents. The generation of plausible trajectories can be a significant computational cost for real-time graphics engines, especially in untethered and mobile devices such as portable VR devices. Previous research explores the plausibility and realism of crowd simulations on desktop computers but fails to account the impact it has on immersion. This study explores how the realism of crowd trajectories affects the perceived immersion in VR. We do so by running a psychophysical experiment in which participants rate the realism of real/synthetic trajectories data, showing similar level of perceived realism.

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Cited By

Steed AArcher DBrandstätter KCongdon BFriston SGanapathi PGiunchi DIzzouzi LPark GSwapp DThiel F(2023)Lessons learnt running distributed and remote mixed reality experimentsFrontiers in Computer Science10.3389/fcomp.2022.9663194Online publication date: 5-Jan-2023
https://doi.org/10.3389/fcomp.2022.966319
Bovo RGiunchi DSteed AHeinis T(2022)MR-RIEW: An MR Toolkit for Designing Remote Immersive Experiment Workflows2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)10.1109/VRW55335.2022.00234(766-767)Online publication date: Mar-2022
https://doi.org/10.1109/VRW55335.2022.00234

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Information

Published In

cover image ACM Conferences

VRST '21: Proceedings of the 27th ACM Symposium on Virtual Reality Software and Technology

December 2021

563 pages

ISBN:9781450390927

DOI:10.1145/3489849

Editors:
Yuichi Itoh
Aoyama Gakuin University, Japan
,
Kazuki Takashima
Tohoku University, Japan
,
Parinya Punpongsanon
Osaka University, Japan
,
Misha Sra
University of California, Santa Barbara, USA
,
Kazuyuki Fujita
Tohoku University, Japan
,
Shigeo Yoshida
The University of Tokyo, Japan
,
Tham Piumsomboon
University of Canterbury, New Zealand

Copyright © 2021 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 08 December 2021

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Short-paper
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VRST '21

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VRST '21: 27th ACM Symposium on Virtual Reality Software and Technology

December 8 - 10, 2021

Osaka, Japan

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Cited By

Steed AArcher DBrandstätter KCongdon BFriston SGanapathi PGiunchi DIzzouzi LPark GSwapp DThiel F(2023)Lessons learnt running distributed and remote mixed reality experimentsFrontiers in Computer Science10.3389/fcomp.2022.9663194Online publication date: 5-Jan-2023
https://doi.org/10.3389/fcomp.2022.966319
Bovo RGiunchi DSteed AHeinis T(2022)MR-RIEW: An MR Toolkit for Designing Remote Immersive Experiment Workflows2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)10.1109/VRW55335.2022.00234(766-767)Online publication date: Mar-2022
https://doi.org/10.1109/VRW55335.2022.00234

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