In this paper, we describe an ongoing work towards developing a whole-body interaction interface for exploring different visualizations of movement, using real-time motion capture and 3D models, to apply in dance learning and improvisation within a creative, gamified context. A full inertial motion capture system is used by the performer while a simple user interface provides the option to the user to experiment with different avatars, and visualizations e.g., trace of motions on different parts of the body and to interact with virtual objects. The 3D simulation provides a real-time visual feedback for the movement. The interaction follows the paradigm of moving from mimicking kinetic material into a self-reflection teaching approach. The interactive avatar is the reflection of the performer, but on the same time the avatar depicts a character, a dance partner which can inspire the user who moves to explore different ways of moving. Either within the framework of artistic experimentation and creativity, or in the context of education, the visual metaphors of movement shape and qualities consist a powerful tool and raise many scientific and research questions.

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This paper reports on a small-scale experiment conducted in the Stedelijk Museum Amsterdam (SMA), showcasing the effective use of CHESS research prototype for the creation and provision of personalized interactive museum experiences and highlighting the main results reached.

In this paper we present BalOnSe (named after the ballet step balance), an ontology-based web interface that allows the user to annotate classical ballet videos, with a hierarchical domain specific vocabulary and provides an archival system for videos of dance. The interface integrates a hierarchical vocabulary based on classical ballet syllabus terminology (Ballet.owl) implemented as an OWL-2 ontology. BalOnSe supports the search and browsing of the multimedia content using metadata (title, dancer featured, etc.), and also implements the functionality of "searching by movement concepts", i.e., filtering the videos that are associated with particular required terms of the vocabulary, based on previous submitted annotations. In the paper, we present the ballet.owl ontology, and its structure, explaining the conceptual modeling decisions. We highlight the main functionality of the system and finally, we present how the manual ontology guided annotation allows the user to search the content through the vocabularies and also view statistics in the form of tag clouds.