Abstract
Many problems in image representation and classification involve some form of dimensionality reduction. Non-negative matrix factorization (NMF) is a recently proposed unsupervised procedure for learning spatially localized, parts-based subspace representation of objects. Here we present an improvement of the classical NMF by combining with Log-Gabor wavelets to enhance its part-based learning ability. In addition, we compare the new method with principal component analysis (PCA) and locally linear embedding (LLE) proposed recently in Science. Finally, we apply the new method to several real world datasets and achieve good performance in representation and classification.
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
Martinez, A.M., Benavente, R.: “The AR face database,” CVC Tech. Report #24 (1998)
Liu, C., Wechsler, H.: A Gabor feature classifier for face recognition. In: Proc. 8th IEEE Int. Conf. Computer Vision, Vancouver, BC, Canada, July 9-12 (2001)
Donato, G., Bartlett, M.S., Hager, J.C., et al.: Classifying facial actions. IEEE Trans. Pattern Anal. Machine Intell. 21, 974–989 (1999)
Turk, M., Pentland, A.: Eigenfaces for recognition. Journal of Cognitive neuroscience 3, 71–86 (1991)
Roweis, S.T., Saul, L.K.: Nonlinear dimensionality reduction by locally linear embedding. Science 290(5500), 2323–2326 (2000)
Lee, D., Seung, H.: Learning the parts of objects by non-negative matrix factorization. Nature 401, 788–791 (1999)
Belhumeur, P.N., Hespanha, J.P., Kriegman, D.J.: Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection. IEEE Trans. Pattern Anal. Machine Intell. 19, 711–720 (1997)
Martinez, A., Kak, A.C.: PCA versus LDA. IEEE Trans. Pattern Anal. Machine Intell. 23, 228–233 (2001)
Bishop, C.M., Svensén, M., Williams, C.K.I.: GTM: The general topographic mapping. Neural Computation 10, 215–234 (1998)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zheng, Z., Zhao, J., Yang, J. (2005). NMF with LogGabor Wavelets for Visualization. In: Gagalowicz, A., Philips, W. (eds) Computer Analysis of Images and Patterns. CAIP 2005. Lecture Notes in Computer Science, vol 3691. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11556121_4
Download citation
DOI: https://doi.org/10.1007/11556121_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28969-2
Online ISBN: 978-3-540-32011-1
eBook Packages: Computer ScienceComputer Science (R0)