Shi, Y, Ondrej, J, Wang, H orcid.org/0000-0002-2281-5679 et al. (1 more author) (2017) Shape up! Perception based body shape variation for data-driven crowds. In: 2017 IEEE Virtual Humans and Crowds for Immersive Environments (VHCIE). VHCIE workshop, IEEE Virtual Reality 2017, 19 Mar 2017, Los Angeles, USA. IEEE ISBN 978-1-5386-2758-7
Abstract
Representative distribution of body shapes is needed when simulating crowds in real-world situations, e.g., for city or event planning. Visual realism and plausibility are often also required for visualization purposes, while these are the top criteria for crowds in entertainment applications such as games and movie production. Therefore, achieving representative and visually plausible body-shape variation while optimizing available resources is an important goal. We present a data-driven approach to generating and selecting models with varied body shapes, based on body measurement and demographic data from the CAESAR anthropometric database. We conducted an online perceptual study to explore the relationship between body shape, distinctiveness and attractiveness for bodies close to the median height and girth. We found that the most salient body differences are in size and upper-lower body ratios, in particular with respect to shoulders, waist and hips. Based on these results, we propose strategies for body shape selection and distribution that we have validated with a lab-based perceptual study. Finally, we demonstrate our results in a data-driven crowd system with perceptually plausible and varied body shape distribution.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017, IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 23 Mar 2017 12:42 |
Last Modified: | 17 Jan 2018 03:40 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/VHCIE.2017.7935623 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:113877 |