Header logo is ps

Appealing female avatars from {3D} body scans: Perceptual effects of stylization


Conference Paper


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%.

Author(s): Reuben Fleming and Betty Mohler and Javier Romero and Michael J. Black and Martin Breidt
Book Title: 11th Int. Conf. on Computer Graphics Theory and Applications (GRAPP)
Year: 2016
Month: Febuary

Department(s): Perceiving Systems
Research Project(s): Body Perception
Bibtex Type: Conference Paper (inproceedings)
Paper Type: Conference

Event Place: Rome

Links: pdf


  title = {Appealing female avatars from {3D} body scans: Perceptual effects of stylization},
  author = {Fleming, Reuben and Mohler, Betty and Romero, Javier and Black, Michael J. and Breidt, Martin},
  booktitle = {11th Int. Conf. on Computer Graphics Theory and Applications (GRAPP)},
  month = feb,
  year = {2016},
  month_numeric = {2}