Abstract
In this study, an expression manifold is constructed by Neighborhood Preserving Embedding (NPE) based on the expression semantic metric for a global representation of all possible facial expression images. On this learned manifold, images with semantic ‘similar’ expression are mapped onto nearby points whatever their lighting, pose and individual appearance are quite different. The proposed manifold extracts the universal expression feature and reveals the intrinsic semantic global structure and the essential relations of the expression data. Experimental results demonstrate the effectiveness of our approach.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Pantic, M., Rothkrantz, L.: Automatic Analysis of Facial Expressions: The State of the Art. IEEE Trans. Pattern Analysis and Machine Intelligence 22(12) (2000)
Fasel, B., Luettin, J.: Automatic Facial Expression Analysis: A Survey. Pattern Recognition 36, 259–275 (2003)
Ekman, P.: Emotion in the Human Face. Cambridge University Press, New York (1982)
Seung, H.S., Lee, D.D.: The Manifold Ways of Perception. Science 290, 2268–2269 (2000)
Chang, Y., Hu, C., Turk, M.: Manifold of Facial Expression. In: Proceedings of IEEE International Workshop on Analysis and Modeling of Faces and Gestures, Nice, France (2003)
Elgammal, A., Lee, C.: Separating Style and Content on a Nonlinear Manifold. In: Proc. Computer Vision and Pattern Recognition Conf., Washington (2004)
Roweis, S., Saul, L.K.: Nonlinear Dimensionality Reduction by Locally Linear Embedding. Science 290 (2000)
Tenenbaum, J.B., Silva, V., Langford, J.C.: A Global Geometric Framework for Nonlinear Dimensionality Reduction. Science 290 (2000)
Belkin, M., Niyogi, P.: Laplacian Eigenmaps for Dimensionality Reduction and Data Representation. Neural Computation 15(6), 1373–1396 (2003)
He, X.F., Cai, D., Yan, S.C., Zhang, H.J.: Neighborhood Preserving Embedding. In: IEEE Conf. on ICCV’05, vol. 2, pp. 1208–1213 (2005)
Belhumeur, P.N., Hespanda, J., Kiregeman, D.: Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection. IEEE Trans. on PAMI 19(7), 711–720 (1997)
Kandel, A.: Fuzzy Techniques in Pattern Recognition. Wiley, New York (1982)
Wang, F., Wang, J., Zhang, C., Shen, H.C.: Semi-Supervised Classification Using Linear Neighborhood Propagation. In: Proceedings of Int. Conf. on Computer Vision and Pattern Recognition (2006)
Kanade, T., Cohn, J., Tian, Y.: Comprehensive Database for Facial Expression Analysis. In: Proc. IEEE Inter. Conf. on Face and Gesture Recognition, pp. 46–53 (2000)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Xu, S., Jia, Y., Zhao, Y. (2007). Facial Expression Analysis on Semantic Neighborhood Preserving Embedding. In: Liu, D., Fei, S., Hou, Z., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4492. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72393-6_107
Download citation
DOI: https://doi.org/10.1007/978-3-540-72393-6_107
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72392-9
Online ISBN: 978-3-540-72393-6
eBook Packages: Computer ScienceComputer Science (R0)