A combined probabilistic framework for learning gestures and actions

In this paper we introduce a probabilistic approach to support visual supervision and gesture recognition. Task knowledge is both of geometric and visual nature and it is encoded in parametric eigenspaces. Learning processes for compute modal subspaces (eigenspaces) are the core of tracking and recognition of gestures and tasks. We describe the overall architecture of the system and detail learning processes and gesture design. Finally we show experimental results of tracking and recognition in block-world like assembling tasks and in general human gestures.

Emotion in Cervantes and Shakespeare

Early modern thought found in emotion a key to explaining human behaviour, highlighting the powerful way in which it can influence and disturb human life. Shakespeare’s and Cervantes’s treatment of emotion includes a full acknowledgement of its mental and bodily aspects and functions. But emotion rarely comes in a pure state. Character and emotion interact and their responses are often contradictory. Since emotions are sentiments that we feel and actions that we perform, it is worth inquiring into how, in Cervantes and Shakespeare, emotion affects their characters in different ways.