%Aigaion2 BibTeX export from Idiap Publications
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@ARTICLE{Ba_IEEESMC-B_2008,
                      author = {Ba, Sil{\`{e}}ye O. and Odobez, Jean-Marc},
                    projects = {Idiap, AMIDA, IM2, VACE},
                       month = {2},
                       title = {Recognizing Human Visual Focus of Attention from Head Pose in Meetings},
                     journal = {IEEE Transactions on Systems, Man, Cybernetics, Part-B},
                      volume = {Vol. 39},
                      number = {No. 1},
                        year = {2009},
                    abstract = {We address the problem of recognizing the visual  focus of  attention (VFOA) of meeting participants based on their  head  pose. To this end, the head pose observations are 
modeled using a Gaussian Mixture Model (GMM) or a Hidden Markov Model (HMM) whose hidden states corresponds to the VFOA. The novelties of this work are threefold. First, contrary to previous studies on the topic, in our set-up,  the potential VFOA of a person is not restricted to other participants only. It includes environmental targets as well (a table and a projection screen,',','),
 which increases the complexity of the task, with more VFOA targets spread  in the pan  as well as tilt gaze
space.  Second, we propose a geometric model to set the GMM or HMM parameters by exploiting results from cognitive science on saccadic eye motion, which allows the prediction of the head pose given a gaze target. Third, an unsupervised parameter adaptation step not using any labeled data 
is proposed which accounts for the specific gazing behaviour of each participant.},
                         pdf = {https://publications.idiap.ch/attachments/papers/2008/Ba_IEEESMC-B_2008.pdf}
}