3D face reconstruction based on canonical correlation analysis and morphable model

被引：0
作者：
Hu, Yongli [1 ]
Ge, Yun [1 ]
Sun, Yanfeng [1 ]
Yin, Baocai [1 ]
机构：
[1] Beijing Key Laboratory of Multimedia and Intelligent Software Technology, College of Metropolitan Transportation, Beijing University of Technology
来源：
Journal of Computational Information Systems | 2014年 / 10卷 / 06期
关键词：
3D face reconstruction; Canonical correlation analysis; Morphable model;
D O I：
10.12733/jcis9723
中图分类号：
学科分类号：
摘要：
The traditional 3D face reconstruction method based on morphable model represents facial shape using the knowledge of facial samples. To get good reconstruction result, it is necessary to use enough samples, such as several hundreds of 3D faces. However, for a given facial image, the 3D face reconstruction is a sample dependency problem. Usually the similar samples will achieve good reconstruction result, while the dissimilar samples will give little benefit and even bring distortion. In this paper, we present a 3D face reconstruction method using merely the facial samples related to the given facial image. In the proposed method, the correlations between 2D facial images and 3D faces are firstly established by a training method based on the canonical correlation analysis theory. Then the highly correlated 3D samples of the given facial image are selected according to the correlation distance. Based on these selected samples, a compact 3D morphable model is constructed for 3D face reconstruction. Matching the model with the given facial image, its 3D face is finally reconstructed. The experimental results show that the proposed method has good performance compared with the traditional morphable model. Copyright © 2014 Binary Information Press.
引用
收藏
页码：2405 / 2415
页数：10
相关论文
共 16 条
  • [1] Parke F.I., Parametric model of human faces, (1974)
  • [2] Cohen M., Massara D., Modeling co-articulation in synthetic visual speech, Model and Technique in Computer Animation, pp. 139-156, (1993)
  • [3] Pighin F., Auslander J., Lischinski D., Et al., Realistic Facial Animation Using Image Based 3D Morphing, (1997)
  • [4] Pighin F., Hecker J., Lischinski D., Et al., Synthesizing realistic facial expressions from photographs, Proceedings of SIGGRAPH'98, pp. 75-84, (1998)
  • [5] Pighin F., Modeling and animating realistic faces from images, (1999)
  • [6] Lee W.S., Escher M., Sannier G., Magnenat-Thalmann N., MPEG-4 compatible faces from orthogonal photos, Proceedings of International Conference on Computer Animation, pp. 186-194, (1999)
  • [7] Lee W.S., Kalra P., Magnenat-Thalmann N., Model based face reconstruction for animation, Proceeding of Multimedia Modeling, pp. 323-338, (1997)
  • [8] Lee W.S., Magnenat-Thalmann N., Fast head modeling for animation, Journal Image and Vision Computing, 18, 4, pp. 355-364, (2000)
  • [9] Duan F., Wu F., Zhou M., Et al., Calibrating effective focal length for central catadioptric cameras using one space line, Pattern Recognition Letters, 33, pp. 646-653, (2012)
  • [10] Bowyer K.W., Chang K., Flynn P., A survey of approaches and challenges in 3D and multi-modal 3D + 2D face recognition, Computer Vision and Image Understanding, 101, 1, pp. 1-15, (2006)
12