@conference {Liciotti2014,
	title = {Advanced integration of multimedia assistive technologies: A prospective outlook},
	booktitle = {MESA 2014 - 10th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications, Conference Proceedings},
	year = {2014},
	note = {cited By 0},
	abstract = {In the recent years several studies on population ageing in the most advanced countries argued that the share of people older than 65 years is steadily increasing. In order to tackle this phenomena, a significant effort has been devoted to the development of advanced technologies for supervising the domestic environments and their inhabitants to provide them assistance in their own home. In this context, the present paper aims to delineate a novel, highly-integrated system for advanced analysis of human behaviours. It is based on the fusion of the audio and vision frameworks, developed at the Multimedia Assistive Technology Laboratory (MATeLab) of the Universit{\`a} Politecnica delle Marche, in order to operate in the ambient assisted living context exploiting audio-visual domain features. The existing video framework exploits vertical RGB-D sensors for people tracking, interaction analysis and users activities detection in domestic scenarios. The depth information has been used to remove the affect of the appearance variation and to evaluate users activities inside the home and in front of the fixtures. In addition, group interactions are monitored and analysed. On the other side, the audio framework recognises voice commands by continuously monitoring the acoustic home environment. In addition, a hands-free communication to a relative or to a healthcare centre is automatically triggered when a distress call is detected. Echo and interference cancellation algorithms guarantee the high-quality communication and reliable speech recognition, respectively. The system we intend to delineate, thus, exploits multi-domain information, gathered from audio and video frameworks each, and stores them in a remote cloud for instant processing and analysis of the scene. Related actions are consequently performed.},
	doi = {10.1109/MESA.2014.6935629},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84911977133\&partnerID=40\&md5=3a8fad94ccf6268631dbf553e9360956},
	author = {Daniele Liciotti and Ferroni, G. and Emanuele Frontoni and Squartini, S. and Principi, E. and Bonfigli, R. and Primo Zingaretti and Francesco Piazza}
}
@conference {Fiori1999,
	title = {Efficient architecture for independent component analysis},
	booktitle = {Proceedings - IEEE International Symposium on Circuits and Systems},
	volume = {5},
	year = {1999},
	note = {cited By 0},
	pages = {V-335-V-338},
	abstract = {We present a new independent component analysis technique, based on the information-theoretic approach, implemented by the functional-link network, that allows to separate out mixed independent sub-Gaussian and super-Gaussian source signals. For assessing our theory we present computer simulations performed both on synthetic and real-world data, and compare the performances of the new algorithm with those of the {\textquoteleft}Mixture of Densities{\textquoteright} approach by Xu et al.},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-18544391339\&partnerID=40\&md5=00c2e26050b1438b1cf7de4e2d0f6be0},
	author = {Simone Fiori and Paola Baldassarri and Francesco Piazza}
}
