5,471 research outputs found
Tracking Gaze and Visual Focus of Attention of People Involved in Social Interaction
The visual focus of attention (VFOA) has been recognized as a prominent
conversational cue. We are interested in estimating and tracking the VFOAs
associated with multi-party social interactions. We note that in this type of
situations the participants either look at each other or at an object of
interest; therefore their eyes are not always visible. Consequently both gaze
and VFOA estimation cannot be based on eye detection and tracking. We propose a
method that exploits the correlation between eye gaze and head movements. Both
VFOA and gaze are modeled as latent variables in a Bayesian switching
state-space model. The proposed formulation leads to a tractable learning
procedure and to an efficient algorithm that simultaneously tracks gaze and
visual focus. The method is tested and benchmarked using two publicly available
datasets that contain typical multi-party human-robot and human-human
interactions.Comment: 15 pages, 8 figures, 6 table
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Information acquisition using eye-gaze tracking for person-following with mobile robots
In the effort of developing natural means for human-robot interaction (HRI), signifcant amount of research has been focusing on Person-Following (PF) for mobile robots. PF, which generally consists of detecting, recognizing and following people, is believed to be one of the required functionalities for most future robots that share their environments with their human companions. Research in this field is mostly directed towards fully automating this functionality, which makes the challenge even more tedious. Focusing on this challenge leads research to divert from other challenges that coexist in any PF system. A natural PF functionality consists of a number of tasks that are required to be implemented in the system. However, in more realistic life scenarios, not all the tasks required for PF need to be automated. Instead, some of these tasks can be operated by human operators and therefore require natural means of interaction and information acquisition. In order to highlight all the tasks that are believed to exist in any PF system, this paper introduces a novel taxonomy for PF. Also, in order to provide a natural means for HRI, TeleGaze is used for information acquisition in the implementation of the taxonomy. TeleGaze was previously developed by the authors as a means of natural HRI for teleoperation through eye-gaze tracking. Using TeleGaze in the aid of developing PF systems is believed to show the feasibility of achieving a realistic information acquisition in a natural way
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