FLEMING, Reuben, MOHLER, Betty, ROMERO, Javier, BLACK, Michael J. and BREIDT, Martin (2017). Appealing avatars from 3D body scans: Perceptual effects of stylization. In: BRAZ, Jose, MAGUENAT-THALMANN, Nadia, RICHARD, Paul, LINSEN, Lars, TELEA, Alexandru, BATTIATO, Sebastiano and IMAI, Francisco, (eds.) Computer vision, imaging and computer graphics theory and applications. 11th intenational joint conference, VISIGRAPP 2016, Rome, Italy, February 27-29 2016, revised selected papers. Communications in computer and information science (693). Springer International Publishing, 175-196.
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Abstract
Advances in 3D scanning technology allow us to create realistic virtual avatars from full body 3D scan data. However, negative reactions to some realistic computer generated humans suggest that this approach might not always provide the most appealing results. Using styles derived from existing popular character designs, we present a novel automatic stylization technique for body shape and colour information based on a statistical 3D model of human bodies. We investigate whether such stylized body shapes result in increased perceived appeal with two different experiments: One focuses on body shape alone, the other investigates the additional role of surface colour and lighting. Our results consistently show that the most appealing avatar is a partially stylized one. Importantly, avatars with high stylization or no stylization at all were rated to have the least appeal. The inclusion of colour information and improvements to render quality had no significant effect on the overall perceived appeal of the avatars, and we observe that the body shape primarily drives the change in appeal ratings. For body scans with colour information, we found that a partially stylized avatar was most effective, increasing average appeal ratings by approximately 34%.
Item Type: | Book Section |
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Additional Information: | Series ISSN 1865-0929 |
Identification Number: | https://doi.org/10.1007/978-3-319-64870-5_9 |
Page Range: | 175-196 |
Depositing User: | Helen Garner |
Date Deposited: | 26 Jan 2016 14:48 |
Last Modified: | 18 Mar 2021 06:23 |
URI: | https://shura.shu.ac.uk/id/eprint/11507 |
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