Next Article in Journal
The Use of Fiber Bragg Grating Sensors in Biomechanics and Rehabilitation Applications: The State-of-the-Art and Ongoing Research Topics
Previous Article in Journal
A Real-Time Cardiac Arrhythmia Classification System with Wearable Sensor Networks
Sensors 2012, 12(10), 12870-12889; doi:10.3390/s121012870

3D Face Modeling Using the Multi-Deformable Method

Department of Electrical and Electronics Engineering, Yonsei University, 134 Shinchon-dong, Seodaemun-gu, Seoul 120-749, Korea
* Author to whom correspondence should be addressed.
Received: 24 July 2012 / Revised: 14 September 2012 / Accepted: 19 September 2012 / Published: 25 September 2012
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [1250 KB, 21 June 2014; original version 21 June 2014]   |   Browse Figures


In this paper, we focus on the problem of the accuracy performance of 3D face modeling techniques using corresponding features in multiple views, which is quite sensitive to feature extraction errors. To solve the problem, we adopt a statistical model-based 3D face modeling approach in a mirror system consisting of two mirrors and a camera. The overall procedure of our 3D facial modeling method has two primary steps: 3D facial shape estimation using a multiple 3D face deformable model and texture mapping using seamless cloning that is a type of gradient-domain blending. To evaluate our method’s performance, we generate 3D faces of 30 individuals and then carry out two tests: accuracy test and robustness test. Our method shows not only highly accurate 3D face shape results when compared with the ground truth, but also robustness to feature extraction errors. Moreover, 3D face rendering results intuitively show that our method is more robust to feature extraction errors than other 3D face modeling methods. An additional contribution of our method is that a wide range of face textures can be acquired by the mirror system. By using this texture map, we generate realistic 3D face for individuals at the end of the paper.
Keywords: 3D face modeling; face deformable model; face shape estimation; statistical face model 3D face modeling; face deformable model; face shape estimation; statistical face model
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Share & Cite This Article

Further Mendeley | CiteULike
Export to BibTeX |
MDPI and ACS Style

Hwang, J.; Yu, S.; Kim, J.; Lee, S. 3D Face Modeling Using the Multi-Deformable Method. Sensors 2012, 12, 12870-12889.

View more citation formats

Related Articles

Article Metrics

For more information on the journal, click here


Cited By

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert