Marker-based motion capture systems that stream precise movement data in real-time afford interaction scenarios that can be subtle, detailed, and immediate. However, challenges to effectively utilizing this data include having to build bespoke processing systems which may not scale well, and a need for higher-level representations of movement and movement qualities. We present modosc, a set of Max abstractions for computing motion descriptors from raw motion capture data in real time. Modosc is designed to address the data handling and synchronization issues that arise when working with complex marker sets, and to structure data streams in a meaningful and easily accessible manner. This is achieved by adopting a multiparadigm programming approach using o.dot and Open Sound Control. We describe an initial set of motion descriptors, the addressing system employed, and design decisions and challenges.
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