@article {2184,
	title = {Designing and Evaluating a Social Gaze-Control System for a Humanoid Robot },
	journal = {IEEE Transactions on Human-Machine Systems },
	volume = {44},
	year = {2014},
	pages = {157-168},
	keywords = {Robotics},
	author = {A. Zaraki and D. Mazzei and Giuliani, M. and D. De Rossi}
}
@article {2189,
	title = { Development and Testing of a Multimodal Acquisition Platform for Human-Robot Interaction Affective Studies},
	journal = {Journal of Human robot Interaction },
	volume = {3},
	year = {2014},
	pages = {1-24},
	keywords = {Robotics},
	doi = { http://dx.doi.org/10.5898/JHRI.3.2.Lazzeri},
	url = {http://humanrobotinteraction.org/journal/index.php/HRI/article/view/142/pdf_3},
	author = {Lazzeri, N. and D. Mazzei and D. De Rossi}
}
@conference {2186,
	title = {An Experimental Eye-Tracking Study for the Design of a Context-Dependent Social Robot Blinking Model},
	booktitle = {Living Machines 2014},
	year = {2014},
	pages = {356-366},
	publisher = {Springer-Verlag},
	organization = {Springer-Verlag},
	address = {Milan, Italy, July 30 {\textendash} August 1},
	abstract = {<p>uman gaze and blinking behaviours have been recently considered, to empower humanlike robots to convey a realistic behaviour in a social human-robot interaction. This paper reports the findings of our investigation on human eye-blinking behaviour in relation to human gaze behaviour, in a human-human interaction. These findings then can be used to design a humanlike eye-blinking model for a social humanlike robot. In an experimental eye-tracking study, we showed to 11 participants, a 7-minute video of social interactions of two people, and collected their eye-blinking and gaze behaviours with an eye-tracker. Analysing the collected data, we measured information such as participants{\textquoteright} blinking rate, maximum and minimum blinking duration, number of frequent (multiple) blinking, as well as the participants{\textquoteright} gaze directions on environment. The results revealed that participants{\textquoteright} blinking rate in a social interaction are qualitatively correlated to the gaze behaviour, as higher number of gaze shift increased the blinking rate. Based on the findings of this study, we can propose a context-dependent blinking model as an important component of the robot{\textquoteright}s gaze control system that can empower our robot to mimic human blinking behaviour in a multiparty social interaction.</p>
},
	keywords = {Robotics},
	doi = {10.1007/978-3-319-09435-9_31},
	url = {http://link.springer.com/chapter/10.1007/978-3-319-09435-9_31},
	author = {A. Zaraki and Dehkordi, M. B. and D. Mazzei and D. De Rossi}
}
@conference {2185,
	title = {I-CLIPS Brain: A Hybrid Cognitive System for Social Robots },
	booktitle = { Living Machines 2014},
	year = {2014},
	pages = {213-224},
	publisher = {Springer-Verlag},
	organization = {Springer-Verlag},
	address = { Milan, Italy, July 30 {\textendash} August 1},
	abstract = {<p>Sensing and interpreting the interlocutor{\textquoteright}s social behaviours is a core challenge in the development of social robots. Social robots require both an innovative sensory apparatus able to perceive the {\textquotedblleft}social and emotional world{\textquotedblright} in which they act and a cognitive system able to manage this incoming sensory information and plan an organized and pondered response. In order to allow scientists to design cognitive models for this new generation of social machines, it is necessary to develop control architectures that can be easily used also by researchers without technical skills of programming such as psychologists and neuroscientists. In this work an innovative hybrid deliberative/reactive cognitive architecture for controlling a social humanoid robot is presented. Design and implementation of the overall architecture take inspiration from the human nervous system. In particular, the cognitive system is based on the Damasio{\textquoteright}s thesis. The architecture has been preliminary tested with the FACE robot. A social behaviour has been modeled to make FACE able to properly follow a human subject during a basic social interaction task and perform facial expressions as a reaction to the social context.</p>
},
	keywords = {Robotics},
	isbn = {978-3-319-09434-2},
	doi = {10.1007/978-3-319-09435-9_19},
	url = {http://link.springer.com/chapter/10.1007/978-3-319-09435-9_19},
	author = {D. Mazzei and Cominelli, L. and Lazzeri, N. and A. Zaraki and D. De Rossi}
}
@conference {2187,
	title = {Recognition and Expression of Emotions by a Symbiotic Android Head},
	booktitle = {IEEE-RAS International Conference on Humanoid Robots (HUMANOIDS 2014)},
	year = {2014},
	pages = {134 - 139 },
	publisher = {IEEE},
	organization = {IEEE},
	address = {Madrid, Spain, November 18 - 20},
	keywords = {Bioengineering, Robotics},
	doi = {10.1109/HUMANOIDS.2014.7041349},
	author = {D. Mazzei and A. Zaraki and Lazzeri, N. and D. De Rossi}
}
@conference {2188,
	title = {An RGB-D Based Social Behavior Interpretation System for a Humanoid Social Robot},
	booktitle = {IEEE-RSI International Conference on Robotics and Mechatronics 2014 },
	year = {2014},
	pages = {185 - 190},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Tehran, Iran, October 15-17},
	keywords = {Bioengineering, Robotics},
	doi = {10.1109/ICRoM.2014.6990898},
	author = {A. Zaraki and Giuliani, M. and Dehkordi, M. B. and D. Mazzei and D{\textquoteright}Ursi, A. and D. De Rossi}
}
