Abstract
We propose a hierarchical scheme of tracking facial regions in video sequences. The hierarchy uses the face structure, facial regions and their components, such as eyes and mouth, to achieve improved robustness against structural deformations and the temporal loss of image components due to, e.g., self-occlusion. The temporal deformation of facial eye regions is mapped to estimate the head orientation around the yaw axis. The performance of the algorithm is demonstrated for free head motions.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Baker, S., Matthews, I.: Lucas-Kanade 20 years on: A unifying framework: Part1. Carnegie-Mellon Univ., Robotics Institute, CMU-RI-TR-02-16 (2002)
Black, M.J., Yacoob, Y.: Recognizing facial expressions in image sequences using local parametrized models of image motion. Int.’l J. of Computer Vision 25, 23–48 (1997)
Essa, I.A., Pentland, A.P.: Facial expression recognition using a dynamic model and motion energy. In: Proc. 5th Int.’l Conf. on Computer Vision, ICCV 1995, pp. 360–367 (1995)
Gee, A., Cipolla, R.: Determining the gaze of faces in images. Image and Vision Comp. 30, 639–647 (1994)
Krüger, N., Pötzsch, M., von der Malsburg, C.: Determination of face position and pose with a learned representation based on labeled graphs. Im. Vis. Comput. 15(8), 665–673 (1997)
Lucas, B.D., Kanade, T.: An iterative image registration technique with an application to stereo vision. In: Proc. 7th Int.’l Conf. on Artif. Intell., IJCAI 1981, pp. 674–679 (1981)
Rae, R., Ritter, H.J.: Recognition of human head orientation based on artificial neural networks. IEEE Trans. on Neural Networks 9, 257–265 (1998)
Tan, K.-H., Kriegman, D.J., Ahuja, N.: Appearance-based eye gaze estimation. In: Proc. 6th IEEE Workshop on Applications of Computer Vision, WACV 2002, pp. 191–195 (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Bausch, T., Bayerl, P., Neumann, H. (2006). Multi-level Face Tracking for Estimating Human Head Orientation in Video Sequences. In: André, E., Dybkjær, L., Minker, W., Neumann, H., Weber, M. (eds) Perception and Interactive Technologies. PIT 2006. Lecture Notes in Computer Science(), vol 4021. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11768029_18
Download citation
DOI: https://doi.org/10.1007/11768029_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34743-9
Online ISBN: 978-3-540-34744-6
eBook Packages: Computer ScienceComputer Science (R0)