posted on 2019-06-10, 08:57authored byGholamreza Anbarjafari, R.E. Haamer, I. Lusi, T. Tikk, L. Valgma
The use of virtual reality (VR) has been exponentially increasing and due to that many researchers have started to work on developing
new VR based social media. For this purpose it is important to have an avatar of the user which look like them to be easily generated by the
devices which are accessible, such as mobile phones. In this paper, we propose a novel method of recreating a 3D human face model captured
with a phone camera image or video data. The method focuses more on model shape than texture in order to make the face recognizable. We
detect 68 facial feature points and use them to separate a face into four regions. For each area the best fitting models are found and are further
morphed combined to find the best fitting models for each area. These are then combined and further morphed in order to restore the original
facial proportions. We also present a method of texturing the resulting model, where the aforementioned feature points are used to generate
a texture for the resulting model.
Funding
This work has been partially supported
by Estonian Research Council Grants (PUT638), The Scientific
and Technological Research Council of Turkey (TÜBİTAK)
(Proje 1001‒116E097), the Estonian Centre of Excellence in
IT (EXCITE) funded by the European Regional Development
Fund and the European Network on Integrating Vision and Language (iV&L Net) ICT COST Action IC1307.
History
School
Loughborough University London
Published in
The Bulletin of the Polish Academy of Sciences: Technical Sciences
Volume
67
Pages
125 - 132
Citation
ANBARJAFARI, G. ... et al., 2019. 3D face reconstruction with region based best fit blending using mobile phone for virtual reality based social media. The Bulletin of the Polish Academy of Sciences: Technical Sciences, 67(1), pp. 125 - 132.
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/
Publication date
2019
Notes
This is an Open Access Article. It is published by Polish Academy of Sciences under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/