1 |
M. Piccardi, "Background subtraction techniques: A review," in Proc. IEEE Int. Conf. Syst., Man Cybern., The Hague, The Netherlands, vol. 4, pp. 3099-3104, Oct. 2004.
|
2 |
Y. Benezeth, P.-M. Jodoin, B. Emile, H. Laurent, and C. Rosenberger, "Comparative study of background subtraction algorithms," Journal of Electronic Imaging, Vol. 19, No. 3, pp. 1-12, 2010.
|
3 |
R. Rodriguez-Gomez, E. J. Fernandez-Sanchez, J. Diaz, and E. Ros, "FPGA implementation for real-time background subtraction based on horprasert model," Sensors, vol. 12, no. 1, pp. 585-611, Jan. 2012.
DOI
|
4 |
D. Lee, "Effective Gaussian mixture learning for video background subtraction," IEEE Trans. Pattern Anal. Mach. Intell., vol. 27, no. 5, pp. 827-832, May 2005.
DOI
|
5 |
C. Stauffer and E. Grimson, "Adaptive background mixture models for real-time tracking," in Proc. IEEE Int. Conf. Comput. Vis. Pattern Recognit., Ft. Collins, CO, vol. 2, pp. 246-252, Jun. 1999.
|
6 |
M.V. Droogenbroeck, O. Paquot, Background subtraction: experiments and improvements for vibe, in IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 32-37, 2012.
|
7 |
Z. Zivkovic, "Improved adaptive gaussian mixture model for background subtraction," in Proc. IEEE Int. Conf. Pattern Recognition, Cambridge, U.K., vol. 2, pp. 28-31, Aug. 2004.
|
8 |
A. Elgammal, R. Duraiswami, D. Harwood, and L. Davis, "Background and foreground modeling using nonparametric kernel density estimation for visual surveillance," Proc. IEEE, vol. 90, no. 7, pp. 1151-1163, Jul. 2002.
DOI
|
9 |
M. K. Chowdary, S. S. Babu and H. Khan, "FPGA Implementation of Moving Object Detection in Frames by Using Background Subtraction Algorithm," in Proceedings of the International conference on Communication and Signal Processing (ICCSP), Melmaruvathur, Tamilnadu, India, pp. 1032-1036, 2013.
|
10 |
N. Goyette. P. Jodoin, F. Porikli, J. Konrad and P. Ishwar. "Changedetection.net: A new change detection benchmark dataset," Proc. IEEE Conf. Computer Vision and Pattern Recognition Workshops, pp. 16-21. 2012.
|
11 |
M. Hofmann, P. Tiefenbacher, and G. Rigoll. Background segmentation with feedback: The pixel-based adaptive segmenter, In IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 38-43, 2012.
|