Abstract
In this paper we propose a method for automating the process of detecting regions of motion in a video sequence in real time. The main idea of this work is to detect motion based on both structure and color. The detection using structure is carried out with the aid of information gathered from the Census Transform computed on gradient images based on Sobel operators. The Census Transform characterizes local intensity patterns in an image region. Color-based detection is done using color histograms, which allow efficient characterization without prior assumptions about color distribution in the scene. The probabilities obtained from the gradient-based Census Transform and from Color Histograms are combined in a robust way to detect the zones of active motion. Experimental results demonstrate the effectiveness of our approach.
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
Froba, B., Ernst, A.: Face detection with the modified census transform. In: Sixth IEEE International Conference on Automatic Face and Gesture Recognition, Erlangen, Germany, May 2004, p. 91–96 (2004)
Funt, B.V., Finlayson, G.D.: Color constant color indexing. IEEE Transaction on Pattern Analysis and Machine Intelligence 17(5), 522–529 (1995)
Heisele, B., Kressel, U., Ritter, W.: Tracking non-rigid, moving objects based on color cluster flow. In: Proceedings of 1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Juan, Puerto Rico, June 1997, pp. 257–260 (1997)
Huwer, S., Niemann, H.: Adaptive change detection for real-time surveillance applications. In: Third IEEE International Workshop on Visual Surveillance, Dublin, Ireland, pp. 37–46 (2000)
Jang, D., Choi, H.-I.: Moving object tracking using active models. In: Proceedings of 1998 International Conference on Image Processing (ICIP 98), vol. 3, pp. 648–652 (October 1998)
Just, A., Rodriguez, Y., Sebastien, M.: Hand posture classification and recognition using the modified census transform. In: Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition (FGR 2006), pp. 351–356 (2006)
McKennaa, S.J., Raja, Y., Gong, S.: Tracking colour objects using adaptive mixture models. Image and Vision Computing 17(3/4), 225–231 (1999)
Monnet, A., Mittal, A., Paragios, N., Ramesh, V.: Background modeling and subtraction of dynamic scenes. In: ICCV 2003: Proceedings of the Ninth IEEE International Conference on Computer Vision, Washington, DC, USA, pp. 1305–1312 (2003)
Nakamura, T., Ogasawara, T.: Online visual learning method for color image segmentation and object tracking. In: Proceedings of 1999 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 1999), vol. 1, pp. 222–228 (1999)
Ren, Y., Chua, C.-S.: Motion detection with non-stationary background. In: Proceedings of the 11th International Conference on Image Analysis and Processing, Palermo, Italy (September 2001)
Stauffer, C., Grimson, W.E.L.: Adaptive background mixture models for real time tracking. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, p. 252 (1999)
Stein, F.: Efficient computation of optical flow using the census transform. In: Rasmussen, C.E., Bülthoff, H.H., Schölkopf, B., Giese, M.A. (eds.) DAGM 2004. LNCS, vol. 3175, pp. 79–86. Springer, Heidelberg (2004)
Swain, M.J., Ballard, D.H.: Color indexing. International Journal of Computer Vision 7(1), 11–32 (1991)
Yamada, K., Mochizuki, K., Aizawa, K., Saito, T.: Motion segmentation with census transform. In: Shum, H.-Y., Liao, M., Chang, S.-F. (eds.) PCM 2001. LNCS, vol. 2195, pp. 903–908. Springer, Heidelberg (2001)
Zabih, R., Woodfill, J.: Non-parametric local transforms for computing visual correspondence. In: European Conference on Computer Vision, Stockholm, Sweden, May 1994, pp. 151–158 (1994)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chakraborty, M., Fuentes, O. (2009). Real-Time Image-Based Motion Detection Using Color and Structure. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2009. Lecture Notes in Computer Science, vol 5627. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02611-9_67
Download citation
DOI: https://doi.org/10.1007/978-3-642-02611-9_67
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02610-2
Online ISBN: 978-3-642-02611-9
eBook Packages: Computer ScienceComputer Science (R0)