A component based deformable model for generalized face alignment

Proceedings of the IEEE International Conference on Computer Vision

Volumn , Issue , 2007, Pages

  Huang, Yuchi ^a   Liu, Qingshan ^a,b   Metaxas, Dimitris ^a  

^a RUTGERS UNIVERSITY   (United States)

^b INSTITUTE OF AUTOMATION   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER NETWORKS; COMPUTER VISION; IMAGE PROCESSING; STATISTICAL METHODS; TRELLIS CODES;

COMPONENT BASED; DEFORMABLE MODELING; FACE ALIGNMENT; INTERNATIONAL CONFERENCES;

DEFORMATION;

EID: 50649103931     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2007.4409017     Document Type: Conference Paper

References (20)

1. T. Cootes, C. Taylor, and J. Graham. Active shape models: their training and application, 1995. Computer Vision and Image Understanding.
2. T. F. Cootes and C. Taylor. A mixture model for representing shape variation, 1999. Image and Vision Computing, 17(8).
3. J. Coughlan and S. Ferreira. Finding deformable shapes using loopy belief propagation, 2002. In The Seventh European Conference on Computer Vision, Copenhagen, Denmark.
4. M. M. Fleck. Some defects in finite-difference edge finders. IEEE Trans. on PAMI, No. 3, Vol. 14. March 1992. pp 337-345.
5. W. T. Freeman, E. C. Pasztor, and O. T. Carmichael. Learning low-level vision. International Journal of Computer Vision, 40(1):25-47, 2000.
6. A. S. Georghiades and P. N. Belhumeur. From few to many: Illumination cone models for face recognition under variable lighting and pose. IEEE Trans. PAMI, Vol. 23, No. 6, pp 643-660, 2001.
7. K. Grochow, S. Martin, A. Hertzmann, and Z. Popovi. Style-based inverse kinematics, 2004. ACM Proc. SIGGRAPH., August 2004.
8. Y. Huang, S. Lin, S. Li, H. Lu, and H. Shum. Face alignment under variable illumination. International Conference on Automatic Face and Guesture, 2004.
9. D. J. Jobson. Properties and performance of a center surround retinex. IEEE Trans. on Image Proc, Vol. 6, No. 3, 1997, pp. 451-462.
10. N. D. Lawrence. Gaussian process latent variable models for visualization of high dimensional data, 2003. In NIPS, 2003.
11. N. D. Lawrence. Probabilistic non-linear principal component analysis with gaussian process latent variable models, 2005. in Journal of Machine Learning Research 6, pp 1783-1816.
12. L. Liang, F. Wen, X. Tang, and Y. Xu. An integrated model for accurate shape alignment, 2006. In ECCV, volume IV, pages 333C346, Graz, Austria.
13. L. Liang, F.Wen, Y.-Q. Xu, X. Tang, and H.-Y. Shum. Accurate face alignment using shape constrained markov network, 2006. CVPR (1) 1313-1319.
14. C. Liu, S. Zhu, and H. Shum. Learning inhomogeneous gibbs model of faces by minimax entropy, 2001. In IEEE Intl Conf. on Computer Vision, Vancouver, Canada.
15. S. Romdhani, S. Cong, and A. Psarrou. A multi-view nonlinear active shape model using kernel pca, 1999. In 10th British Machine Vision Conference, Nottingham, UK, Sept. 1999.
16. T. Sim and S. Baker. The cmu pose, illumination, and expression data-base. Proc. IEEE Int. Conf. on Auto. Face and Gesture Recog, May, 2002.
17. P. Viola and M. Jones. Robust real-time object detection. International Journal of Computer Vision, 2002.
18. L. Wiskott, J. Fellous, N. Kruger, and C. der Malsburg. Face recognition by elastic bunch graph matching, 1997. In ICIP,Santa Barbara.
19. T. Zhang and D. Freedman. Tracking objects using density matching and shape priors, 2003. In ICCV, Nice, France.
20. Y. Zhou, L. Gu, and H. Zhang. Bayesian tangent shape model: Estimating shape and pose parameters via bayesian inference, 2003. IEEE Conf. on Computer Vision and Pattern Recognition Madison, WI, June 2003.