Automatic Recognition and Generation of Affective Movements

author of this thesis. This is a true copy of the thesis, including any required final revisions, as accepted by my examiners. I understand that my thesis may be made electronically available to the public. ii Body movements are an important non-verbal communication medium through which affective states of the demonstrator can be discerned. For machines, the capability to recognize affective expressions of their users and generate appropriate actuated responses with recognizable affective content has the potential to improve their life-like attributes and to create an engaging, entertaining, and empathic human-machine interaction. This thesis develops approaches to systematically identify movement features most salient to affective expressions and to exploit these features to design computational mod-els for automatic recognition and generation of affective movements. The proposed ap-proaches enable 1) identifying which features of movement convey affective expressions, 2) the automatic recognition of affective expressions from movements, 3) understandin