Working in the Motion Capture Lab at University of California, Irvine

Motion capture is the animation technique of measuring a subject's position and orientation in three-dimensional space over time and recording that data in a computer. Motion tracking involves real-time sensing of location, speed, duration and various other characteristics of movement, often as part of an interactive system.

I am concerned with exploring its current state, comparing it to other capture techniques (such as digital video and image processing techniques), and the way in which dancers, researchers, and audiences respond to figures created from "realistic" and "non-realistic" motion capture (that is, characters or abstract imagery that is based on the performance of live dancers).

My current projects in this area are: (1) building a motion capture library, (2) exploring various forms of interactive multimedia presentations in which the viewer can make selections and structure their own mapping of movement and sound, (3) developing innovative forms of computer animation based on the integration of motion capture data with visual effects software, and (4) motion-flow scripting as a new paradigm for structuring choreography in digital applications (virtual dance).

At University of California Irvine, Claire Trevor School of the Arts, Department of Dance, I established an area of motion capture research and course study centered on dance and choreographic applications. Motion capture techniques are valuable to the dance field not only for collecting or documenting the positions, quality and style of dance, but because the motion information could be used by other dance artists and researchers at a later time to develop their own sense of articulation and choreographic order from the original data.

This motion capture research is in the initial phase of integration with Active Space environments, telematic performance (with particular focus on Internet 2 performances and collaboration) and the practice of "distributed choreography". As a continuation of my ongoing research in motion capture, and collaboration with software designers in motion capture, I ask: How can motion capture data be used to highlight nuance in dance?

My research also investigates virtual dance can be created from small fragments and developed into a motion flow network which serves as a score. Given a series of fragments (movement phrases), the question become, What motion flow networks are possible? In a motion flow network, each fragment is represented by a box (run, fall, twist, etc.). How these fragments are organized into a motion flow network, and what kind of behaviors are assigned to the figures or crowds (seek, repel, avoid) in that fragment, is in development.