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Automatic human behaviour understanding

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During social interactions we express ourselves not only through words but also through facial expressions, tone of voice, gesture and body posture. However, today’s computers are still unable to reliably read and understand such non-verbal signals. Better automatic analysis of human behaviour has numerous applications in the fields of human computer interaction, education and healthcare. In this talk I will explore the challenges we still face in automatic human behaviour understanding and the ways to address them. First, I will talk about capturing the temporal and spatial relationships inherent to human behaviour through the use of novel probabilistic models. Second, I will discuss the use of multiple types of behaviour signals to improve sensing performance. Finally, I will outline the importance of modelling such behaviour in context for further progression of the field.

This talk is part of the Rainbow Group Seminars series.

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