Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 31103
Face Reconstruction and Camera Pose Using Multi-dimensional Descent

Authors: Varin Chouvatut, Suthep Madarasmi, Mihran Tuceryan


This paper aims to propose a novel, robust, and simple method for obtaining a human 3D face model and camera pose (position and orientation) from a video sequence. Given a video sequence of a face recorded from an off-the-shelf digital camera, feature points used to define facial parts are tracked using the Active- Appearance Model (AAM). Then, the face-s 3D structure and camera pose of each video frame can be simultaneously calculated from the obtained point correspondences. This proposed method is primarily based on the combined approaches of Gradient Descent and Powell-s Multidimensional Minimization. Using this proposed method, temporarily occluded point including the case of self-occlusion does not pose a problem. As long as the point correspondences displayed in the video sequence have enough parallax, these missing points can still be reconstructed.

Keywords: gradient descent, Camera Pose, Face Reconstruction, Powell's Multidimensional Minimization

Digital Object Identifier (DOI):

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1246


[1] W. H. Press, S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery, "Numerical Recipes - The Art of Scientific Computing," 3rd ed., Cambridge, 2007.
[2] C. B. Barber, D. P. Dobkin, and H. Huhdanpaa, "The Quickhull Algorithm for Convex Hulls," ACM Transactions on Mathematical Software, vol. 22, no. 4, pp. 469-483, Dec 1996.
[3] V. Chouvatut and S. Madarasmi, "A Comparison of Two Camera Pose Methods for Augmented Reality," 7th IASTED International Conference on Signal and Image Processing (SIP), pp. 554-559, 15-17 Aug 2005.
[4] V. Chouvatut and S. Madarasmi, "Estimation of Camera Pose for Use in Augmented Reality System," 20th International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC), Vol. 3, pp. 979-980, 4-7 Jul 2005.
[5] R.Y. Tsai, "A Versatile Camera Calibration Technique for High- Accuracy 3D Machine Vision Metrology Using Off-the-Shelf TV Camera and Lenses," IEEE Journal of Robotics and Automation, Vol. RA-3, Issue 4, pp. 323-344, Aug 1987.
[6] H. Kato and M. Billinghurst, "Marker Tracking and HMD Calibration for a Video-Based Augmented Reality Conferencing System," Proceeding 2nd IEEE and ACM International Workshop on Augmented Reality, pp. 85-94, Oct 1999.
[7] T. Okuma, K. Sakaue, H. Takemura, and N. Yokoya, "Real- Time Camera Parameter Estimation from images for a Mixed Reality System," IEEE Proceeding 15th International Conference on Pattern Recognition, Vol. 4, pp. 482-486, 3-7 Sep 2000.
[8] R. I. Hartley, "Projective Reconstruction and Invariants from Multiple Images," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 16, Issue 10, pp. 1036-1041, Oct 1994.
[9] S. Avidan and A. Shashua, "Novel View Synthesis by Cascading Trilinear Tensors," IEEE Transactions on Visualization and Computer Graphics, Vol. 4, Issue 4, pp. 293- 306, Oct-Dec 1998.
[10] R. Hartley and A. Zisserman, "Multiple View Geometry in Computer Vision," 2nd ed., Cambridge, 2006.
[11] J. Li and R. Chellappa, "A Factorization Method for Structure from Planar Motion", IEEE Workshop on Motion and Video Computing (WACV/MOTIONS), Vol. 2, pp. 154-159, Jan 2005.
[12] N. B. Karayiannis, "Reformulated Radial Basis Neural Networks Trained by Gradient Descent", IEEE Transactions on Neural Networks, Vol. 10, Issue 3, pp. 657-671, May 2000.
[13] O.T.-C. Chen, "Motion Estimation Using a One-Dimensional Gradient Descent Search", IEEE Transactions on Circuits and Systems for Video Technology, Vol. 10, Issue 4, pp. 608-616, Jun 2000.
[14] J.J. Guerrero and C. Sagues, "Estimating the Motion Direction from Brightness Gradient on Lines", IEEE Transactions on Systems, Man, and Cybernetics - Part C: Applications and Reviews, Vol. 31, Issue 3, pp. 419-426, Aug 2001.
[15] L.M. Po, K.H. Ng, K.W. Cheung, K.M. Wong, Y. Uddin, and C.W. Ting, "Novel Directional Gradient Descent Searches for Fast Block Motion Estimation", IEEE Transactions on Circuits and Systems for Video Technology, Vol. 19, Issue 8, pp. 1189- 1195, Aug 2009.
[16] A. Smolic, "Robust Generation of 360-Degree Panoramic Views from Consumer Video Sequences", 4th EURASIP-IEEE Region 8 International Symposium on Video/Image Processing and Multimedia Communications (VIPromCom), pp. 431-435, 16-19 Jun 2002.
[17] A.M. Sasson, "Combined Use of the Powell and Fletcher - Powell Nonlinear Programming Methods for Optimal Load Flows", IEEE Transactions on Power Apparatus and Systems, Vol. PAS-88, Issue 10, pp. 1530-1537, Oct 1969.
[18] X. Xu and R.D. Dony, "Differential Evolution with Powell-s Direction Set Method in Medical Image Registration", IEEE International Symposium on Biomedical Imaging: Nano to Micro, Vol. 1, pp. 732-735, 15-18 Apr 2004.
[19] G.J. Edwards, C.J. Taylor, and T.F. Cootes, "Interpreting Face Images using Active Appearance Models", 3rd IEEE International Conference on Automatic Face and Gesture Recognition, pp. 300-305, 14-16 Apr 1998.
[20] T.F. Cootes, G.J. Edwards, and C.J. Taylor, "Active Appearance Models", International Proceedings European Conference on Computer Vision, Vol. 2, pp. 484-498, 1998.
[21] S. W. Park, J. Heo, and M. Savvides, "3D Face Reconstruction from a Single 2D Face Image," IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR), pp. 1-8, 23-28 Jun 2008.
[22] Y. Zheng, J. Chang, Z. Zheng, and Z. Wang, "3D Face Reconstruction from Stereo: A Model Based Approach," IEEE International Conference on Image Processing (ICIP), Vol. 3, pp. III-65 - III-68, 16 Sep 2007 - 19 Oct 2007.
[23] Y. Zheng and Z. Wang, 2008, "Robust Depth Estimation for Efficient 3D Face Reconstruction," 15th IEEE International Conference on Image Processing, pp. 1516-1519, 12-15 Oct 2008.