Incremental unsupervised-learning of appearance manifold with view-dependent covariance matrix for face recognition from video sequences

IEICE Transactions on Information and Systems

Volumn E92-D, Issue 4, 2009, Pages 642-652

  Lina, ^a   Takahashi, Tomokazu ^b   Ide, Ichiro ^a   Murase, Hiroshi ^a  

^a NAGOYA UNIVERSITY   (Japan)

^b GIFU SHOTOKU GAKUEN UNIVERSITY   (Japan)

Author keywords

Appearance manifold; Eigenspace; Incremental learning; Video based face recognition; View dependent covariance matrix

Indexed keywords

COVARIANCE MATRIX; UNSUPERVISED LEARNING; VIDEO RECORDING;

APPEARANCE MANIFOLDS; EIGENSPACES; INCREMENTAL LEARNING; VIDEO-BASED FACE RECOGNITION; VIEW-DEPENDENT;

FACE RECOGNITION;

EID: 77950348049     PISSN: 09168532     EISSN: 17451361     Source Type: Journal    
DOI: 10.1587/transinf.E92.D.642     Document Type: Article

References (16)

1. M. Kirby and L. Sirovich, "Application of the Karhunen-Loeve procedure for the characterization of human face, " IEEE Trans. Pattern Anal. Mach. Intell., vol. 12, no. 1, pp. 103-108, Dec. 1990.
2. M. Turk and A. Pentland, "Face recognition using eigenfaces, " Proc. IEEE Conf. on Computer Vision and Pattern Recognition, pp. 586-591, Maui HI, USA, June 1991.
3. H. Murase and S. K. Nayar, "Visual learning and recognition of 3-D objects from appearance, " Int. J. Comput. Vis., vol. 14, no. 1, pp. 5-24, Jan. 1995.
4. H. Murase and S. K. Nayar, "Illumination planning for object recognition using parametric eigenspaces, " IEEE Trans. Pattern Anal. Mach. Intell., vol. 16, no. 12, pp. 1219-1227, Dec. 1994.
5. B. Moghaddam and A. Pentland, "Probabilistic visual learning for object representation, " IEEE Trans. Pattern Anal. Mach. Intell., vol. 19, no. 7, pp. 696-710, July 1997. (Pubitemid 127762262)
6. A. M. Martinez, "Recognition of partially occluded and/or imprecisely localized faces using a probabilistic approach, " Proc. IEEE Conf. on Computer Vision and Pattern Recognition, vol. 1, pp. 712-717, Hilton Head Island SC, USA, June 2000.
7. Y. Chang, C. Hu, and M. Turk, "Probabilistic expression analysis on manifolds, " Proc. IEEE Conf. on Computer Vision and Pattern Recognition, vol. 2, pp. 520-527, Washington DC, USA, July 2004.
8. C. M. Christoudias and T. Darrel, "On modeling nonlinear shapeand-texture appearance manifolds, " Proc. IEEE Conf. on Computer Vision and Pattern Recognition, vol. 2, pp. 1067-1074, San Diego CA, USA, June 2005. (Pubitemid 43897476)
9. B. J. Frey, M. Jojic, and A. Kannan, "Learning appearance and transparency manifolds of occluded objects in layers, " Proc. IEEE Conf. on Computer Vision and Pattern Recognition, vol. 1, pp. 45-52, Madison WI, USA, June 2003.
10. Lina, T. Takahashi, I. Ide, and H. Murase, "Appearance manifold with embedded covariance matrix for robust 3D object recognition, " Proc. IAPR Conf. on Machine Vision Applications 2007, pp. 504-507, Tokyo, Japan, May 2007.
11. Lina, T. Takahashi, I. Ide, and H. Murase, "Construction of appearance manifold with embedded view-dependent covariance matrix for 3D object recognition, " IEICE Trans. Inf. & Syst., vol. E91-D, no. 4, pp. 1091-1100, April 2008.
12. B. Raytchev and H. Murase, "Unsupervised recognition of multiview face sequences based on pairwise clustering with attraction and repulsion, " Comput. Vis. Image Understand., vol. 91, no. 1-2, pp. 22-52, 2003.
13. S. Zhou and R. Chellappa, "Probabilistic human recognition from video, " Proc. European Conf. on Computer Vision, vol. 3, pp. 681-697, Copenhagen, Denmark, May 2002.
14. K.-C. Lee, J. Ho, M.-H. Yang, and D. Kriegman, "Visual tracking and recognition using probabilistic appearance manifolds, " Comput. Vis. Image Understand., vol. 99, no. 3, pp. 303-331, 2005.
15. J. Ho, M.-H. Yang, J. Lim, K.-C. Lee, and D. Kriegman, "Clustering appearances of objects under varying illumination conditions, " Proc. IEEE Conf. on Computer Vision and Pattern Recognition, vol. 1, pp. 11-18, Madison WI, USA, June 2003.
16. X. Liu and T. Chen, "Video-based face recognition using adaptive hidden Markov models, " Proc. IEEE Conf. on Computer Vision and Pattern Recognition, vol. 2, pp. 26-33, Madison WI, USA, June 2003.