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We address the problem of recognizing, in dynamic meetings in which people do not remain seated all the time, the visual focus of attention (VFOA) of seated people from their head pose and contextual activity cues. We propose a model that comprises the VFOA of a meeting participant as the hidden state, and his head pose as the observation. To account for the presence of moving visual targets due to...
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 correspond to the VFOA. The novelties of this paper are threefold. First, contrary to previous studies on the topic, in our setup, the...
We address the problem of recognizing the visual focus of attention (VFOA) of meeting participants from their head pose and contextual cues. The main contribution of the paper is the use of a head pose posterior distribution as a representation of the head pose information contained in the image data. This posterior encodes the probabilities of the different head poses given the image data, and constitute...
This paper presents investigations on visual focus of attention (VFOA) recognition in meetings from audio-visual perceptual cues. Rather than independently recognizing the VFOA of each participant from his own head pose, we propose to recognize participants' VFOA jointly in order to introduce context dependent interaction models that relates to group activity and the social dynamics of communication...
In this paper, we define and address the problem of finding the visual focus of attention for a varying number of wandering people (VFOA-W), determining where a person is looking when their movement is unconstrained. The VFOA-W estimation is a new and important problem with implications in behavior understanding and cognitive science and real-world applications. One such application, presented in...
Head pose estimation is a research area which has many applications, e.g. in human computer interfaces design or in the analysis of people's focus-of-attention. The paper addresses the issue of head pose estimation, and makes two contributions. First it introduces a database of more than 2 hours of video with head pose annotation involving people engaged in office activities or meeting discussion...
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