An Ontology of Virtual Humans: incorporating semantics into human shapes

Most of the efforts concerning graphical representations of humans (Virtual Humans) have been focused on synthesizing geometry for static or animated shapes. The next step is to consider a human body not only as a 3D shape, but as an active semantic entity with features, functionalities, interaction skills, etc. In the framework of the AIM@SHAPE Network of Excellence we are currently working on an ontology-based approach to make Virtual Humans more active and understandable both for humans and machines. The ontology for Virtual Humans we are defining will provide the ”semantic layer” required to reconstruct, stock, retrieve and reuse content and knowledge related to Virtual Humans. The connection between the semantic and the graphical data is achieved thanks to an intermediate layer based on anatomical features extracted from morphological shape analysis. The resulting shape descriptors can be used to derive higherlevel descriptors from the raw geometric data. High-level descriptors can then be used to control human models.