Human-humanoid interaction by an intentional system

The paper describes a framework for developing of an intentional vision system oriented to human-humanoid interaction. Such system will be able to recognize user faces, to recognize and tracking human postures by visual perception. The described framework is organized on two modules mapped on the corresponding outputs to obtain: intentional perception of faces; intentional perception of human body movements. Moreover a possible integration of intentional vision module in a complete cognitive architecture is proposed, and knowledge management and reasoning is allowed by a suitable OWL-DL ontology. In particular, the ontological knowledge approach is employed for human behaviour and expression comprehension while stored user habits are used for building a semantically meaningful structure for perceiving the human wills. A semantic description of user wills is formulated in terms of the symbolic features produced by the intentional vision system. The sequences of symbolic features belonging to a domain specific ontology are employed to infer human wills, and to perform suitable actions.