CORRESPONDENCE: BiometricsNo Access
A BOOSTED MANIFOLD LEARNING FOR AUTOMATIC FACE RECOGNITION
https://doi.org/10.1142/S0218001410007919Cited by:6 (Source: Crossref)
Abstract
Manifold learning is an effective dimension reduction method to extract nonlinear structures from high dimensional data. Recently, manifold learning has received much attention within the research communities of image analysis, computer vision and document data analysis. In this paper, we propose a boosted manifold learning algorithm towards automatic 2D face recognition by using AdaBoost to select the best possible discriminating projection for manifold learning to exploit the strength of both techniques. Experimental results support that the proposed algorithm improves over existing benchmarks in terms of stability and recognition precision rates.
Keywords:
References
- Patt. Recogn. Lett. 28(14), 1885 (2007), DOI: 10.1016/j.patrec.2006.12.018. Crossref, Web of Science, Google Scholar
- Comput. Vis. Patt. Recogn. 14, 268 (2004). Google Scholar
- IEEE Trans. Patt. Anal. Mach. Intell. 19(7), 711 (1997), DOI: 10.1109/34.598228. Crossref, Web of Science, Google Scholar
-
M. Belkin and P. Niyogi , Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering ,Advances in Neural Information Processing System 15 ( 2001 ) . Google Scholar - D. Cai, X. He and J. Han, Using graph model for face analysis, Technical Report, UIUCDCS-R-2005-2636, UIUC (2005) . Google Scholar
Y. Chang , C. Hu and M. Turk , Probabilistic expression analysis on manifolds, Proc. IEEE Computer Society Conf. Computer Vision and Pattern Recognition (CVPR 04) (2004) pp. 520–527. Google ScholarH. Chang , D. Y. Yeung and Y. Xiong , Super-resolution through neighbor embedding, Proc. Conf. Computer Vision and Pattern Recognition (CVPR 04) (2004) pp. 275–282. Google ScholarH. T. Chen , H.-W. Chang and T.-L. Liu , Local discriminant embedding and its variants, Proc. IEEE Computer Society Conf. Computer Vision and Pattern Recognition (2005) pp. 846–853. Google ScholarA. Elgammal and C. S. Lee , Inferring 3D body pose from silhouettes using activity manifold learning, Proc. IEEE Computer Society Conf. Computer Vision and Pattern Recognition (CVPR 04) (2004) pp. 681–688. Google Scholar- Patt. Recogn. Lett. 27, 861 (2006), DOI: 10.1016/j.patrec.2005.10.010. Crossref, Web of Science, Google Scholar
- J. Comput. Syst. Sci. 55(1), 119 (1997), DOI: 10.1006/jcss.1997.1504. Crossref, Web of Science, Google Scholar
- J. Japanese Soc. Artif. Intell. 14(5), 771 (1999). Web of Science, Google Scholar
X. He , Neighborhood preserving embedding, Proc. Tenth IEEE Int. Conf. Computer Vision (2005) pp. 1208–1213. Google Scholar- X. He and P. Niyogi, Locality Preserving Projections, Advances in Neural Information Processing Systems (2003) . Google Scholar
- IEEE Trans. Patt. Anal. Mach. Intell. 27(3), 328 (2005). Web of Science, Google Scholar
X. Huang , S. Z. Li and Y. Wang , Learning with cascade for classification of non-convex manifolds, Comput. Vision Patt. Recogn. Workshop (2004) p. 66. Google Scholar- IEEE Trans. Patt. Anal. Mach. Intell. 28, 497 (2006), DOI: 10.1109/TPAMI.2006.77. Crossref, Web of Science, Google Scholar
- Int. J. Patt. Recogn. Artif. Intell. 22(3), 389 (2008), DOI: 10.1142/S0218001408006272. Link, Web of Science, Google Scholar
- Patt. Recogn. 38(10), 1705 (2005). Crossref, Web of Science, Google Scholar
- IEEE Trans. Patt. Anal. Mach. Intell. 29(7), 1262 (2007), DOI: 10.1109/TPAMI.2007.1033. Crossref, Web of Science, Google Scholar
- IEEE Trans. Pattern Anal. Mach. Intell. 22(10), 1090 (2000), DOI: 10.1109/34.879790. Crossref, Web of Science, Google Scholar
C. Qing and J. Jiang , Recognition of JPEG compressed face images based on AdaBoost, 2nd Int. Conf. Semantics and Digital Media Technologies (2007) pp. 272–275. Google Scholar- Int. J. Patt. Recogn. Artif. Intell. 22(3), 411 (2008), DOI: 10.1142/S0218001408006302. Link, Web of Science, Google Scholar
- Science 290(22), 2323 (2000), DOI: 10.1126/science.290.5500.2323. Crossref, Web of Science, Google Scholar
R. E. Schapire , The boosting approach to machine learning an overview, Proc. Mathermatical Sciences Research Institute (MSRI) Workshop on Nonlinear Estimation and Classification (Berkeley, California, 2001) pp. 149–172. Google ScholarR. E. Schapire and Y. Singer , Improved boosting algorithms using confidence-rated predictions, Proc. Eleventh Ann. Conf. Computational Learning Theory (1998) pp. 80–91. Google Scholar- , Advances in Kernel Methods — Support Vector Learning, eds.
B. Scholkopf , C. Burges and A. Smola (MIT Press, Cambridge, MA, 1999) pp. 327–352. Google Scholar - Int. J. Patt. Recogn. Artif. Intell. 22(3), 515 (2008), DOI: 10.1142/S0218001408006296. Link, Web of Science, Google Scholar
- Int. J. Patt. Recogn. Artif. Intell. 22(3), 445 (2008), DOI: 10.1142/S0218001408006284. Link, Web of Science, Google Scholar
P. Silapachote , D. R. Karuppiah and A. R. Hanson , Feature selection using Adaboost for face expression recognition, Proc. Fourth IASTED Int. Conf. Visualization, Imag. Imag. Process. (2004) pp. 84–89. Google Scholar- Science 290(5500), 2319 (2000), DOI: 10.1126/science.290.5500.2319. Crossref, Web of Science, Google Scholar
- , Boosting multiple classifiers constructed by hybrid discriminant analysis ,
Lecture Notes in Computer Science 3541 , eds.N. C. Oza ( Springer-Verlag , 2005 ) . Crossref, Google Scholar - J. Cogn. Neurosci. 3(1), 71 (1991), DOI: 10.1162/jocn.1991.3.1.71. Crossref, Web of Science, Google Scholar
P. Viola and M. J. Jones , Rapid object detection using a boosted cascade of simple features, IEEE Computer Society Conf. Computer Vision and Pattern Recognition (2001) pp. 511–518. Google Scholar- Int. J. Comput. Vis. 57(2), 137 (2004), DOI: 10.1023/B:VISI.0000013087.49260.fb. Crossref, Web of Science, Google Scholar
- Yale University, database available from: http://cvc.yale.edu/projects/yalefaces/yalefaces.html . Google Scholar
- Yale University, database available from: http://cvc.yale.edu/projects/yalefacesB/yalefacesB.html . Google Scholar
- IEEE Trans. Patt. Anal. Mach. Intell. 29(1), 40 (2007), DOI: 10.1109/TPAMI.2007.250598. Crossref, Web of Science, Google Scholar
P. Yang , Face recognition using ada-boosted gabor features, Proc. Sixth IEEE Int. Conf. Automatic Face and Gesture Recognition (2004) pp. 356–361. Google Scholar-
H. Zha and Z. Zhang , Isometric embedding and continuum isomap , Proc. Twentieth Int. Conf. Machine Learning ( 2003 ) . Google Scholar - ACM Comput. Surv. 35(4), 399 (2003), DOI: 10.1145/954339.954342. Crossref, Web of Science, Google Scholar
