Spectral-360: A physics-based technique for change detection

IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

Volumn , Issue , 2014, Pages 405-408

  Sedky, Mohamed ^a   Moniri, Mansour ^a   Chibelushi, Claude C ^a  

^a STAFFORDSHIRE UNIVERSITY   (United Kingdom)

Author keywords

background modelling; change detection; colour constancy; image formation models

Indexed keywords

COLOR; COMPUTER VISION; REFLECTION;

BACKGROUND MODELLING; CHANGE DETECTION; COLOR DESCRIPTORS; COLOUR CONSTANCY; IMAGE FORMATION MODELS; OBJECTIVE EVALUATION; SPECTRAL REFLECTANCES; STATE-OF-THE-ART METHODS;

IMAGE SEGMENTATION;

EID: 84908544148     PISSN: 21607508     EISSN: 21607516     Source Type: Conference Proceeding    
DOI: 10.1109/CVPRW.2014.65     Document Type: Conference Paper

References (12)

1. M. Sedky, M. Moniri and C. C. Chibelushi, "Classification of smart video surveillance systems for commercial applications, " Proceedings of IEEE International Conference on Advanced Video and Signal Based Surveillance, pp. 638-643, 2005.
2. G. J. Klinker, S. A. Shafer, and T. Kanade, "A physical approach to colour image understanding, " in: International Journal on Computer Vision, vol. 4, no. 1, pp. 7-38, 1990.
3. J. Parkkinen, J. Hallikainen and T. Jaaskelainen, "Characteristic spectra of Munsell colours, " in: Journal of the Optical Society of America A, vol. 6, no. 2, pp. 318-322, 1989.
4. McCamy and S. Calvin. "Correlated colour temperature as an explicit function of chromaticity coordinates, " in: Journal of Colour Research & Application, vol. 17, no. 2, pp. 142-144, 1992.
5. http://www. eureca. de/datasheets/01. xx. XXXx/01. 02. XXXx/01. 02. 0185/I CX098BQ. pdf (31th of March 2014, date last accessed)
6. S. H. Cha, "Comprehensive survey on distance/similarity measures between probability density functions, " International Journal of Mathematical Models and Methods in Applied Sciences, City, 1(2), 1, pp. 300-307, 2007.
7. N. Goyette, P.-M. Jodoin, F. Porikli, J. Konrad, and P. Ishwar, "changedetection. net: A new change detection benchmark dataset, " in Proc. IEEE Workshop on Change Detection (CDW-2012) at CVPR-2012, 2012.
8. Z. Zivkovic, F. van der Heijden, "Efficient adaptive density estimation per image pixel for the task of background subtraction"Pattern Recognition Letters, vol. 27, no. 7, pp. 773-780, 2006.
9. C. Stauffer and W. E. L. Grimson, "Adaptive background mixture models for real-time tracking, " in Proc. Int. Conf. on Computer Vision and Pattern Recognition, Vol. 2, 1999.
10. A. Elgammal, D. Harwood, and L. Davis, "Non-parametric model for background subtraction, " in Proc. Eur. Conf. on Computer Vision, Lect. Notes Comput. Sci. 1843, 751-767 2000.
11. Y. Benezeth, P.-M. Jodoin, B. Emile, H. Laurent, and C. Rosenberger. "Comparative study of background subtraction algorithms" in. J. of Elec. Imaging, vol., no. 3, pp. 1-12, 2010.
12. Z. Zivkovic, "Improved adaptive Gaussian mixture model for background subtraction, " in Proc. Int. Conf. Pattern Recognition, pp. 28-31, IEEE, Piscataway, NJ 2004.