@article {Ezzahout20139,
	title = {An efficient people tracking system using the FFT-Correlation and Optimized SAD},
	journal = {Journal of Theoretical and Applied Information Technology},
	volume = {48},
	number = {1},
	year = {2013},
	note = {cited By 1},
	pages = {9-14},
	abstract = {The research questions which this study addresses are resumed in obtaining the picks of Optimized SAD and FFT-Correlation function. These values allow us to detect and track the blocs corresponding to the moving person. This Bloc-Matching system of our tracked bloc 8x8, simplify the process of detecting and tracking all the representative matrix of foreground. Practically, in this correspondence, we propose an implementation technique for detection and tracking system which detect and track people{\textquoteright}s in motion using a fixed single camera. These bi-techniques simplify the process of people tracking and give a new way for people tracking. Moreover, in this system we choose to detect moving people with the more robust algorithm (Gaussian Mixture Model) in term of misclassified pixels. Thereafter, we track a bloc 8x8 from the bounding box containing the moving person by returning the position of the similar bloc in the next frame. This bloc position is detected by maximization of the Fast Fourier Transform-Correlation (FFT-Corr) and minimizing the error: optimized Sum of Absolute Difference (OSAD) between the bloc reference and the similar bloc. {\textcopyright} 2005 - 2013 JATIT \& LLS. All rights reserved.},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84876021321\&partnerID=40\&md5=cfb2300d8d0e312b0c77d271b683b278},
	author = {Ezzahout, A.a and Hadi, M.Y.b and Thami, R.O.H.a}
}
@conference {Hdioud2013,
	title = {A real-time people tracking system based on trajectory estimation using single field of camera view},
	booktitle = {International Conference on Computer Applications Technology, ICCAT 2013},
	year = {2013},
	note = {cited By 1},
	abstract = {Object detection is a crucial step for video surveillance systems. In this paper, we propose to detect moving objects in video sequences. Under the assumption that our camera is fixed, we use first subtracting the background to extract moving objects. From the detected foreground we applied the Harris corner detector to identify points of interest on the moving object. The analysis of connected components detected by subtracting the background allows grouped the pixels of moving objects in order to extract the center of gravity to draw the trajectory of the objects present in the scene. {\textcopyright} 2013 IEEE.},
	doi = {10.1109/ICCAT.2013.6522038},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84879848181\&doi=10.1109\%2fICCAT.2013.6522038\&partnerID=40\&md5=2a15bc75e155d914dfa1c1ff16398266},
	author = {Hdioud, B.a and Ezzahout, A.a and Hadi, Y.a b and Haj Thami, R.O.a}
}
