Abstract
In this paper, we tackle the shadow problem in depth for a better foreground segmentation. We propose a novel variant of co-training technique for shadow detection and removal in uncontrolled scenes. This variant works according to a powerful temporal behavior. Setting co-training parameters is based on an extensive experimental study. The proposed co-training variant runs periodically to obtain more generic classifier, thus improving speed and classification accuracy. An experimental study by quantitative, qualitative and comparative evaluations shows that the proposed method can detect shadow robustly and remove the ‘cast’ part accurately from videos recorded by a static camera and under several constraints.
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
Wang, Y., Wang, S.: Shadow Detection of urban color aerial images based on partial differential equations. In: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XXXVII, part B2 (2008)
Dian, W.: The research on a mixtrue gausssian based clustering algorithm of make background model and supressing shadow. Northwestern Polytechnical University (2006)
Horprasert, T., Harwood, D., Davis, L.S.: A statistical approach for real-time robust background subtraction and shadow detection. In: ICCV Frame-Rate Workshop, vol. 99, pp. 1–19 (1999)
Joshi, A.J., Papanikolopoulos, N.P.: Learning to Detect Moving Shadows in Dynamic Environments. IEEE Transactions on Pattern Analysis and Machine Intelligence 30(11), 2055–2063 (2008)
Finlayson, G.D., Hordley, S.D., Drew, M.S.: Removing Shadows from Images Using Retinex. In: The 10th Color Imaging Conference: Color Science and Engineering Systems, Technologies, Applications, Scottsdale, Arizona, pp. 73–79 (2002)
Wang, J.M., Chung, Y.C., Chang, C.L.: Shadow detection and removal for traffic images. In: IEEE International Conference on Networking, Sensing and Control, vol. 1, pp. 649–654 (2004)
Liu, H., Yang, C., Shu, X., Wang, Q.: A new method of shadow detection based on edge information and HSV color information. In: 2nd Conference on Power Electronics and Intelligent Transportation System, vol. 1, pp. 286–289 (2009)
Cucchiara, R., Grana, C., Piccardi, M., Prati, A.: Detecting objects, shadows and ghosts in video streams by exploiting color and motion information. In: Proceedings 11th International Conference on Image Analysis and Processing, pp. 360–365 (2001)
Hammami, M., Jarraya, S.K., Ben-Abdallah, H.: On line Background Modeling For Moving Object Segmentation in Dynamic Scenes. Multimedia Tools and Applications Journal (2011); available in SpringerLink, appear first on-line
Jarraya, K.S., Ghorbel, A., Chaouachi, A., Hammami, M.: ROADGUARD Highway Control and Management System. In: Proceedings of the International Conference on Computer Vision Theory and Applications, pp. 632–637 (2011)
Schohn, G., Cohn, D.: Less is More: Active Learning with Support Vector Machines. In: Proceedings of the Seventeenth International Conference on Machine Learning, pp. 839–846 (2000)
Guggenberger, A.: Semi-supervised Learning With Support Vector Machines. Technischen Universität Wien (2008)
Quinlan, J.R.: Induction of Decision Trees. Machine Learning 1(1), 81–106 (1986)
Kononenko, I.: Estimating attributes: Analysis and extensions of relief. In: Proceeding ECML 1994 Proceedings of the European Conference on Machine Learning on Machine Learning, pp. 171–182 (1994)
Zhu, X.: Semi-Supervised Learning Literature Survey, New York. Technical Report (2008)
Quinlan, J.R.: C4.5: Programs for Machine Learning. Morgan Kanfmann Publishers, Inc., Los Altos (1993)
Prati, A., Mikic, I., Trivedi, M.M., Cucchiara, R.: Detecting moving shadows: algorithms and evaluation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 918–923 (2003)
Mikic, I., Cosman, P.C., Kogut, G.T., Trivedi, M.M.: Moving shadow and object detection in traffic scenes. In: 15th International Conference on Pattern Recognition, pp. 321–324 (2000)
Joshi, A.J., Atev, S., Masoud, O., Papanikolopoulos, N.: Moving Shadow Detection with Low- and Mid-Level Reasoning. In: IEEE International Conference on Robotics and Automation, pp. 4827–4832 (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Jarraya, S.K., Boukhriss, R.R., Hammami, M., Ben-Abdallah, H. (2012). Cast Shadow Detection Based on Semi-supervised Learning. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2012. Lecture Notes in Computer Science, vol 7324. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31295-3_3
Download citation
DOI: https://doi.org/10.1007/978-3-642-31295-3_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31294-6
Online ISBN: 978-3-642-31295-3
eBook Packages: Computer ScienceComputer Science (R0)