@article {Iazzi2016156,
	title = {A new method for fall detection of elderly based on human shape and motion variation},
	journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
	volume = {10073 LNCS},
	year = {2016},
	note = {cited By 0},
	pages = {156-167},
	abstract = {Fall detection for elderly and patient has been an active research topic due to the great demand for products and technology of fall detection in the healthcare industry. Computer vision provides a promising solution to analyze personal behavior and detect certain unusual events such as falls. In this paper, we present a new method for fall detection based on the variation of shape and motion. First, we use the CodeBook method to extract the person silhouette from the video. Then, information of rectangle, ellipse and histogram projection are used to provide features to analyze the person shape. In addition, we represent the person shape by three blocks extracted from rectangle. Then, we use optical flow to analyze the person motion within each blocks. Finally, falls are detected from normal activities using thresholding-based method. All experiments show that our fall detection system achieves very good performances in accuracy and error rate. {\textcopyright} Springer International Publishing AG 2016.},
	doi = {10.1007/978-3-319-50832-0_16},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85007364688\&doi=10.1007\%2f978-3-319-50832-0_16\&partnerID=40\&md5=4ed27ef63754e531149224bda59c8227},
	author = {Iazzi, A.a and Rziza, M.a and Thami, R.O.H.a b and Aboutajdine, D.a}
}
@conference {Bouirouga2013422,
	title = {Neural network adult videos recognition using jointly face shape and skin feature extraction},
	booktitle = {VISAPP 2013 - Proceedings of the International Conference on Computer Vision Theory and Applications},
	volume = {1},
	year = {2013},
	note = {cited By 0},
	pages = {422-425},
	abstract = {This paper presents a novel approach for video adult detection using face shape, skin threshold technique and neural network. The goal of employing skin-color information is to select the appropriate color model that allows verifying pixels under different lighting conditions and other variations. Then, the output videos are classified by neural network. The simulation shows that this system achieved 95.4\% of the true rate.},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84878245129\&partnerID=40\&md5=efe58b6bdb1387e7884a28b2a0f6f0bb},
	author = {Bouirouga, H.a and Elfkihi, S.b and Jilbab, A.c and Aboutajdine, D.a}
}
@article {Jorio2013717,
	title = {A new clustering algorithm for wireless sensor networks},
	journal = {Journal of Theoretical and Applied Information Technology},
	volume = {49},
	number = {3},
	year = {2013},
	note = {cited By 1},
	pages = {717-724},
	abstract = {Wireless sensor networks have recently become an attractive research area. However, saving energy and, thus, extending the wireless sensor network lifetime entails great challenges. For this reason, clustering techniques are largely made use of. In this paper we propose a new algorithm based on the principle of spectral clustering methods. Especially, we use the K-ways spectral clustering algorithm. The main characteristic of our proposal is that it defines the optimal number of clusters and dynamically changes the election probabilities of the cluster heads based on their residual energy. Up on analyzing the impact of node density on the robustness of the proposed algorithm as well as on its energy and lifetime gains, simulation results show that the approach actually improves the lifetime of a whole network and presents more energy efficiency distribution compared to Low-Energy Adaptive Clustering Hierarch, Centralized Low-Energy Adaptive Clustering Hierarch, and Distance-Energy Cluster Structure approaches. {\textcopyright} 2005 - 2013 JATIT \& LLS. All rights reserved.},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84875692769\&partnerID=40\&md5=ea5125d9aa1b9b5f0b4c870cfad69e2e},
	author = {Jorio, A.a and Fkihi, S.E.b and Elbhiri, B.c and Aboutajdine, D.a}
}
