Modeling focus of attention for meeting indexing
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Detecting who is looking at whom during multiparty interaction is useful for various tasks such as meeting analysis. There are two contributing factors in the formation of where a person is looking at : head orientation and eye orientation. In this poster, we present an experiment aimed at evaluating the potential of head orientation estimation in detecting who is looking at whom, because head orientation can be estimated accurately and robustly with non-intrusive methods while eye orientation can not. Experimental results show that head orientation contributes 68.9% on average to the overall gaze direction, and focus of attention estimation based on head orientation alone can get an average accuracy of 88.7% in a meeting application scenario with four participants. We conclude that head orientation is a good indicator of focus of attention in human computer interaction applications.