Leach, M. and Maddock, S. orcid.org/0000-0003-3179-0263 (2019) An evaluation approach for a physically-based sticky lip model. Computers, 81 (1). 24. ISSN 2073-431X
Abstract
Physically-based mouth models operate on the principle that a better mouth animation will be produced by simulating physically accurate behaviour of the mouth. In the development of these models, it is useful to have an evaluation approach which can be used to judge the effectiveness of a model and draw comparisons against other models and real-life mouth behaviour. This article presents a set of metrics which can be used to describe the motion of the lips, as well as a process for measuring these from video of real or simulated mouths, implemented using Python and OpenCV. As an example, the process is used to evaluate a physically-based mouth model focusing on recreating the stickiness effect of saliva between the lips. The metrics highlight the changes in behaviour due to the addition of stickiness between the lips in the synthetic mouth model and show quantitatively improved behaviour in relation to real mouth movements. The article concludes that the presented metrics provide a useful approach for evaluation of mouth animation models that incorporate sticky lip effects.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | evaluation; facial animation; physically-based; sticky lips |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 19 Mar 2019 10:45 |
Last Modified: | 19 Mar 2019 10:46 |
Status: | Published |
Publisher: | MDPI |
Refereed: | Yes |
Identification Number: | 10.3390/computers8010024 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:143406 |