Abstract
This paper describes a modal method for point-set tracking in motion sequences. The framework for our study is the recently reported dual-step EM algorithm of Cross and HancockĀ [3]. This provides a statistical framework in which the structural arrangement of the point-sets provides constraints on the pattern of correspondences used to estimate alignment parameters. In this paper our representation of point-set structure is based on the point-adjacency matrix. Using ideas from spectral graph-theory, we show how the eigen-vectors of the point-adjacency matrix can be used to compute point correspondence probabilities. We show that the resulting correspondence matching algorithm can be used to track deforming point-sets detected in motion sequences.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Chung, F.R.K.: Spectral Graph Theory. CBMS series 92, AMS Ed. (1997)
Cootes, T.F., Taylor, C.J., Cooper, D.H., Graham, J.: Active Shape Models - Their Training and Application. Computer Vision, Graphics and Image UnderstandingĀ 61, 38ā59 (1995)
Cross, A.D.J., Hancock, E.R.: Graph matching with a dual step EM algorithm. IEEE PAMIĀ 20, 1236ā1253 (1998)
Dempster, A.P., Laird, N.M., Rubin, D.B.: Maximum-likelihood from incomplete data via the EM algorithm. J. Royal Statistical Soc. Ser. B (methodological)Ā 39, 1ā38 (1977)
Jordan, M.I., Jacobs, R.A.: Hierarchical mixtures of experts and the EM algorithm. Neural ComputationĀ 6, 181ā214 (1994)
Sclaroff, S., Pentland, A.P.: Modal Matching for Correspondence and Recognition. IEEE PAMIĀ 17, 545ā661 (1995)
Scott, G.L., Longuet-Higgins, H.C.: An algorithm for associating the features of 2 images. In: Proceedings of the Royal Society of London Series B (Biological), vol.Ā 244, pp. 21ā26 (1991)
Sengupta, K., Boyer, K.L.: Modelbase partitioning using property matrix spectra. Computer Vision and Image UnderstandingĀ 70(2), 177ā196 (1998)
Shapiro, L.S., Brady, J.M.: Feature-based correspondence - an eigenvector approach. Image and Vision ComputingĀ 10, 283ā288 (1992)
Shokoufandeh, A., Dickinson, S.J., Siddiqi, K., Zucker, S.W.: Indexing using a spectralen coding of topological structure. In: Proc. of the IEEE Conf. on Computer Vision and Pattern Recognition, pp. 491ā497 (1999)
Sossa, H., Horaud, R.: Model indexing: the graph-hashing approach. In: Proc. of the IEEE Conf. on Computer Vision and Pattern Recognition, pp. 811ā815 (1992)
Umeyama, S.: An eigen decomposition approach to weighted graph matching problems. IEEE PAMIĀ 10, 695ā703 (1988)
Wilson, R.C., Hancock, E.R.: Structural Matching by Discrete Relaxation. IEEE PAMIĀ 19, 634ā648 (1997)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
Ā© 2000 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Carcassoni, M., Hancock, E.R. (2000). Spectral Correspondence for Deformed Point-Set Matching. In: Nagel, HH., Perales LĆ³pez, F.J. (eds) Articulated Motion and Deformable Objects. AMDO 2000. Lecture Notes in Computer Science, vol 1899. Springer, Berlin, Heidelberg. https://doi.org/10.1007/10722604_11
Download citation
DOI: https://doi.org/10.1007/10722604_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-67912-7
Online ISBN: 978-3-540-44591-3
eBook Packages: Springer Book Archive