Abstract
This paper proposes a road region extraction method based on the motion information of foreground objects and seeded region growing (SRG) algorithm. By learning on a training set of a scene over a period of time, we get the trajectory of moving object, then use SRG algorithm in which the trajectory is used as seed to extract road region. As a result, instead of detecting foreground objects in a conventional pixel by pixel manner, detection can be mainly performed on or near the pixels of road region so as to facilitate and accelerate foreground detection. In addition, the regions outside road region most of the time do not need to be transmitted in visual communication. Experimental results represent the accuracy and usefulness of our proposed method.
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
Cheung, S.-C., Kamath, C.: Robust Techniques for Background Subtraction in Urban Traffic Video. In: Panchanathan, S., Vasudev, B. (eds.) Proc. Elect. Imaging: Visual Comm. Image Proce. 2004 (Part One) SPIE, vol. 5308, pp. 881–892 (2004)
Kim, K., Chalidabhongse, T.H., Harwood, D., Davis, L.: Background Modeling and Subtraction by Codebook Construction. In: Proc. IEEE Int’l Conf. Image Processing, vol. 5, pp. 3061–3064 (2004)
Sheikh, Y., Shah, M.: Bayesian object detection in dynamic scenes. In: CVPR, vol. (1), pp. 74–79 (2005)
Stauffer, C., Grimson, W.E.L.: Adaptive Background Mixture Models for Real-Time Tracking. In: Proc. IEEE CS Conf. Computer Vision and Pattern Recognition, vol. 2, pp. 246–252 (1999)
Wren, C., Azarbaygaui, A., Darrell, T., Pentland, A.: Pfinder: realtime tracking of the human body. IEEE Trans. Pattern Anal. Machine Intell. 19, 780–785 (1997)
Koller, D., Weber, J., Huang, T., Malik, J., Ogasawara, G., Rao, B., Russel, S.: Towards robust automatic traffic scene analysis in real-time. In: Proc. of the International Conference on Pattern Recognition, Israel (November 1994)
Adams, R., Bischof, L.: Seeded region growing. IEEE Transactions on Pattern Analysis and Machine Intelligence 16(6), 641–647 (1994)
Fan, J., Yau, D.K.Y., Elmagarmid, A.K., Aref, W.G.: Automatic image segmentation by integrating color-edge extraction and seeded region growing. IEEE Transactions on Image Processing 10(10), 1454–1466 (2001)
Lipton, A.J., Fujiyoshi, H., Patil, R.S.: Moving target classification and tracking from real-time video. In: Proc. of IEEE Workshop on Applications of Computer Vision, pp. 8–14 (1998)
KaewTraKulPong, P., Bowden, R.: An Improved Adaptive Background Mixture Model for Real-Time Tracking with Shadow Detection. In: Proc. European Workshop Advanced Video Based Surveillance Systems (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
Qin, H., Zain, J.M., Ma, X., Hai, T. (2010). Road Region Extraction Based on Motion Information and Seeded Region Growing for Foreground Detection. In: Zavoral, F., Yaghob, J., Pichappan, P., El-Qawasmeh, E. (eds) Networked Digital Technologies. NDT 2010. Communications in Computer and Information Science, vol 87. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14292-5_14
Download citation
DOI: https://doi.org/10.1007/978-3-642-14292-5_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14291-8
Online ISBN: 978-3-642-14292-5
eBook Packages: Computer ScienceComputer Science (R0)