Abstract
Reliable tracking has been an active research field in the computer vision. This paper presents a probabilistic face tracking method that uses multiple ingredients and integrates tracking from multiple cameras to increase reliability and overcome the occlusion cases. Color and edge ingredients are fused using Bayesian Network and context factors are used to represent the significance of each modality in fusion. We extend our multi-modal tracking method to multi-camera environments where it is possible to track the face of interest well even though the faces are severely occluded or lost due to handoff in some camera views. Desirable tracking results are obtained when compared to those of other tracking method.
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
Birchfield, S.: Elliptical Head Tracking using Intensity Gradients and Color Histogram. In: Proc. CVPR, pp. 232–237 (1998)
Toyama, K., Horvitz, E.: Bayesian modality fusion: Probabilistic integration of multiple vision algrorithms for head tracking. In: Proc. ACCV (2000)
Liu, F., Lin, X., Li, S., Shi, Y.: Multi-Modal Face Tracking Using Bayesian Network. In: IEEE Workshop, AMFG 2003, pp. 135–142 (October 2003)
Nummiaro, K., Koller-Meier, E., Svoboda, T.: Color-based object tracking in multi-camera environments. In: Michaelis, B., Krell, G. (eds.) DAGM 2003. LNCS, vol. 2781, pp. 591–599. Springer, Heidelberg (2003)
Nishihara, H., Thomas, H., Huber, E.: Real-time tracking of People using stereo and motion. In: Proc. SPIE, vol. 2183, pp. 266–273 (1994)
Nummiaro, K., Koller-Meier, E., Van Gool, L.: A Color-Based Particle Filter. In: First International Workshop on Generative-Model-Based Vision, pp. 53–60 (2002)
Viola, P., Jones, M.: Rapid Object Detection using a Boosted Cascade of Simple Features. In: Proc. CVPR 2001 (2001)
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
Kang, HB., Cho, SH. (2005). Multi-modal Face Tracking in Multi-camera Environments. 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_100
Download citation
DOI: https://doi.org/10.1007/11556121_100
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)