Free-body Gesture Tracking and Augmented Reality Improvisation for Floor and Aerial Dance
This work addresses the need for more flexible and responsive interactive performance systems for dancers, though it appears incremental as it builds on existing tracking technologies with specific enhancements.
The paper tackles the problem of interactive performance in floor and aerial dance by developing a system that uses depth sensing and 3-DOF tracking with IR markers to detect and track free movement, enabling dynamic gesture recognition and improvisation. The result is an improved gesture tracking system called Action Graph that automatically captures repeated movement sub-segments from a single sequence, allowing performers to improvise with real-time system responses.
This paper describes an updated interactive performance system for floor and Aerial Dance that controls visual and sonic aspects of the presentation via a depth sensing camera (MS Kinect). In order to detect, measure and track free movement in space, 3 degree of freedom (3-DOF) tracking in space (on the ground and in the air) is performed using IR markers with a method for multi target tracking capabilities added and described in detail. An improved gesture tracking and recognition system, called Action Graph (AG), is described in the paper. Action Graph uses an efficient incremental construction from a single long sequence of movement features and automatically captures repeated sub-segments in the movement from start to finish with no manual interaction needed with other advanced capabilities discussed as well. By using the new model for the gesture we can unify an entire choreography piece by dynamically tracking and recognizing gestures and sub-portions of the piece. This gives the performer the freedom to improvise based on a set of recorded gestures/portions of the choreography and have the system dynamically respond in relation to the performer within a set of related rehearsed actions, an ability that has not been seen in any other system to date.