Machine Learning, Expressive Movement, Interaction Design, Creative Applications

Program Committee
  1. Frederic Bevilacqua
  2. Baptiste Caramiaux
  3. Rebecca Fiebrink
  4. Marco Gillies
  5. Atau Tanaka
Date: Tuesday 1st April and Wednesday 2nd April Website: Machine Learning (ML) is a set of techniques widely used for data analysis and understanding of complex phenomena. A subset of ML methods that are real time or that look at continuous data have been designed to carry out a wide variety of tasks such as gesture recognition, movement prediction, gesture spotting, animation, social signal processing, style generation. These in turn can be applied in diverse areas including novel human computer interaction methods, human robot interaction, musical performance, digital arts and entertainment. All of these application areas involve specific constraints in the design of ML methods, regarding movement complexity (e.g. from symbols to continuous gestures), learning procedure (e.g. from few examples) and realtime inference.