Abstract
Most current video matting methods perform off-line with a high calculation cost and require many user inputs for multiple key frames. In this paper, we present an online video matting method that runs in real-time based on bilayer segmentation. For the first step of the method, we introduce an accurate bilayer segmentation method for extracting the foreground region from the background using color likelihood propagation. For the second step, we perform alpha-matting based on the segmentation result. To enable real-time processing, we modify the conventional Bayesian matting method by using down-sampling and smart initialization, which increase the calculation speed by 5 times while maintaining the quality. Experimental results on various test sequences show the effectiveness of our 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
Kelly, D.: Digital composition. The Coriolis Group (2000)
Chuang, Y.Y., Agarwala, A., Curless, B., Salesin, D.H., Szeliski, R.: Video matting of complex scenes. ACM Transactions on Graphics 21(3), 243–248 (2002)
Chuang, Y.Y., Curless, B., Salesin, D.H., Szeliski, R.: A bayesian approach to digital matting. In: Proc. CVPR, pp. 264–271 (2001)
Pham, V.Q., Takahashi, K., Naemura, T.: Live video segmentation in dynamic backgrounds using thermal vision. In: Proc. Pacific-Rim Symposium on Image and Video Technology, January 2009, pp. 143–154 (2009)
Ahn, J.K., Kim, C.S.: Real-time segmentation of objects from video sequences with non-stationary backgrounds using spatio-temporal coherence. In: Proc. ICIP, pp. 1544–1547 (2008)
Criminisi, A., Cross, G., Blake, A., Kolmogorov, V.: Bilayer segmentation of live video. In: Proc. CVPR, vol. 1, pp. 53–60 (2006)
Boykov, Y., Jolly, M.: Interactive graph cuts for optimal boundary and region segmentation of objects in n-d images. In: Proc. ICCV, vol. I, pp. 105–112 (2001)
Boykov, Y., Kolmogorov, V.: An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision. Trans. PAMI, 1124–1137 (2004)
Shi, J., Tomasi, C.: Good features to track. In: Proc. CVPR, pp. 593–600 (1994)
Bouguet, J.Y.: Pyramidal implementation of the lucas kanade feature tracker. In: OpenCV documentation (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Pham, VQ., Takahashi, K., Naemura, T. (2010). Real-Time Video Matting Based on Bilayer Segmentation. In: Zha, H., Taniguchi, Ri., Maybank, S. (eds) Computer Vision – ACCV 2009. ACCV 2009. Lecture Notes in Computer Science, vol 5995. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12304-7_46
Download citation
DOI: https://doi.org/10.1007/978-3-642-12304-7_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12303-0
Online ISBN: 978-3-642-12304-7
eBook Packages: Computer ScienceComputer Science (R0)