Abstract
We propose a new general approach to the problem of head pose estimation, based on semi-supervised low-dimensional topographic feature mapping. We show how several recently proposed nonlinear manifold learning methods can be applied in this general framework, and additionally, we present a new algorithm, IsoScale, which combines the best aspects of some of the other methods. The efficacy of the proposed approach is illustrated both on a view- and illumination-varied face database, and in a real-world human-computer interface application, as head pose based facial-gesture interface for automatic wheelchair navigation.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Tenenbaum, J.B., de Silva, V., Langford, J.C.: A global geometric framework for nonlinear dimensionality reduction. Science 290, 2319–2323 (2000)
Belkin, M., Niyogi, P.: Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering. Adv. NIPS 15 (2001)
Heinzmann, J., Zelinsky, A.: 3D facial pose and gaze point estimation using a robust real-time tracking paradigm. In: Proc. Int. Workshop on Automatic Face and Gesture Recognition, Nara, pp. 142–147 (1998)
Bichsel, M., Pentland, A.: Automatic interpretation of human head movements, Technical Report No. 186, MIT Media Laboratory, Vision and Modeling Group (1993)
McKenna, S.J., Gong, S.: Real-time face pose estimation. Real-Time Imaging 4, 333–347 (1998)
Okada, K.: Analysis, Synthesis and Recognition of Human Faces with Pose Variations, Ph.D thesis, USC (2001)
He, X., Yan, S., Hu, Y., Zhang, H.J.: Learning a Locality Preserving Subspace for Visual Recognition. In: Proc. 9th ICCV (2003)
Gower, J.: Adding a point to vector diagrams in multivariate analysis. Biometrica 55, 582–585 (1968)
Sammon, J.W.: A nonlinear mapping for data structure analysis. IEEE Transactions on Computers C 18(5), 401–409 (1969)
Tipping, M.M.E., Lowe, D.: Shadow targets: A novel algorithm for topographic projection by radial basis function network. In: Proc. Int. Conf. Artificial Neural Networks, vol. 440, pp. 7–12 (1997)
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
Raytchev, B., Yoda, I., Sakaue, K. (2005). Topographic Feature Mapping for Head Pose Estimation with Application to Facial Gesture Interfaces. In: Sebe, N., Lew, M., Huang, T.S. (eds) Computer Vision in Human-Computer Interaction. HCI 2005. Lecture Notes in Computer Science, vol 3766. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11573425_18
Download citation
DOI: https://doi.org/10.1007/11573425_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29620-1
Online ISBN: 978-3-540-32129-3
eBook Packages: Computer ScienceComputer Science (R0)