A low-cost markerless tracking system for trajectory interpretation

Abstract

The tracking abilities of 1st generation Kinect sensors have been tested over common trajectories of folk dances. Trajectories related errors, including offset, curve shape, noisy points are investigated and mitigated using well-known signal processing filters. Low cost depth trackers can contribute towards the remote tutoring of folk dances, by providing adequate data to instructors and explicit details to the trainees which segments of their dance trajectories need more work.