@conference { ISI:000326649800036,
	title = {Tracking People Through Selected Blocks Using Correlation and Optimized Similarity Measure OSSD},
	booktitle = {2013 8TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS: THEORIES AND APPLICATIONS (SITA)},
	year = {2013},
	note = {8th International Conference on Intelligent Systems - Theories and Applications (SITA), Ecole Mohammadia Ingenieurs, Rabat, MOROCCO, MAY 08-09, 2013},
	publisher = {IEEE; IEEE Morocco Sect; Univ Mohammed V Agdal},
	organization = {IEEE; IEEE Morocco Sect; Univ Mohammed V Agdal},
	abstract = {This letter correspondence exposes results of a simple and appropriate technique for tracking a moving person in a stream captured and stored in a suitable memory. This method is based on research of similar block only in the next frame or on the range of frames in the video sequence in question. The proposed process of tracking people in a single view from one static camera starts like any video surveillance system with background subtraction. Then, a Minimal Boundary Rectangle is used to surround the moving people in each frame. A selected block of 8x8 sizes is used to calculate the values of their entire joint blocks component in the following frames of the used video sequence. Finally, we search the similarity measure: The minimal of the Optimized Sum of Squared Difference and the Fast Fourier Transform Correlation. The same blocks are correlated in the posterior frames corresponding to the minimum error.},
	isbn = {978-1-4799-0299-6},
	author = {Ezzahout, Abderrahmane and Thami, Rachid Oulad Haj and Hadi, Youssef}
}
@conference { ISI:000290179300057,
	title = {Highlights{\textquoteright} Recognition and Learning in Soccer Video by Using Hidden Markov Models and the Bayesian Theorem},
	booktitle = {2009 INTERNATIONAL CONFERENCE ON MULTIMEDIA COMPUTING AND SYSTEMS (ICMCS 2009)},
	year = {2009},
	note = {International Conference on Multimedia Computing and Systems, Ouarzazate, MOROCCO, APR 02-04, 2009},
	pages = {304-308},
	abstract = {Our paper presents a new approach for the recognition of highlights in soccer video. Our contribution consists of the combination of Bayesian theorem inferences and Hidden Markov Models (HMMs). We build HMMs to calculate probabilities that a test video segment belongs to highlight and non highlight classes. Then, we apply the Bayesian theorem on the two previous probabilities. Our system has achieved an accuracy of 95.6\% which is a good result of highlights detection in comparison with other methods.},
	isbn = {978-1-4244-3756-6},
	doi = {10.1109/MMCS.2009.5256682},
	author = {El Ouazzani, Rajae and Thami, Rachid Oulad Haj}
}
@conference { ISI:000241553600078,
	title = {Fundamental region based indexing and classification of Islamic star pattern images},
	booktitle = {IMAGE ANALYSIS AND RECOGNITION, PT 2},
	series = {Lecture Notes in Computer Science},
	volume = {4142},
	year = {2006},
	note = {3rd International Conference on Image Analysis and Recognition, Povoa de Varzim, PORTUGAL, SEP 18-20, 2006},
	pages = {865-876},
	abstract = {In this paper, we propose a new method for the indexing and classification of Islamic Stars Pattern (ISP) images based on rotational symmetry information. A computational model for the extraction of rotational symmetry features is proposed. This model is based on the three following steps. First, we detect the rotation center of the ISP image, then we complete the image structure by using symmetry information. Second, we compute the angle of rotation and number of folds. Finally, we extract the fundamental region, a representative region in the image from which the whole image can be regenerated. A method is also proposed for indexing and classifying ISP images on the basis of the extracted features. The classification algorithm is based on the number of folds. We characterize an image by its fundamental region and by its class which is defined in the classification step. Experiments show promising results either for ISP images classification or indexing. Efforts for the subsequent task of repeated pattern images classification can be significantly reduced.},
	isbn = {3-540-44894-2},
	issn = {0302-9743},
	author = {Djibril, Mohamed Ould and Hadi, Youssef and Thami, Rachid Oulad Haj},
	editor = {Campilho, A and Kamel, M}
}
@conference { ISI:000241429800054,
	title = {Galois{\textquoteright} lattice for video navigation in a DBMS},
	booktitle = {MULTIMEDIA CONTENT REPRESENTATION, CLASSIFICATION AND SECURITY},
	series = {LECTURE NOTES IN COMPUTER SCIENCE},
	volume = {4105},
	year = {2006},
	note = {International Workshop on Multimedia Content Representation, Classification and Security (MRCS 2006), Istanbul, TURKEY, SEP 11-13, 2006},
	pages = {418-425},
	publisher = {Int Assoc Pattern Recognit; Istanbul Tech Univ; TUBITAK},
	organization = {Int Assoc Pattern Recognit; Istanbul Tech Univ; TUBITAK},
	abstract = {Digital visual media encounters many problems related to storage, representation, querying and visual presentation. In this paper, we propose a technique for the retrieval of video from a database on the basis of video shots classified by a Galois{\textquoteright} lattice. The result is a kind of hypermedia that combines both classification and visualization properties in order to navigate between key frames and video segments.},
	isbn = {3-540-39392-7},
	issn = {0302-9743},
	author = {Mbaye, Ibrahima and Martinez, Jose and Thami, Rachid Oulad Haj},
	editor = {Gunsel, B and Jain, AK and Tekalp, AM and Sankur, B}
}
