Processing Motion Capture Data to Achieve Positional Accuracy

In animating an articulated entity with motion capture data, if the reconstruction is based on forward kinematics, there could be a large error in the end-effector position. The inaccuracy becomes conspicuous when the entity makes interactions with the environment or other entities. The frames at which the end-effector position needs to be accurate are designated as “keyframes” (e.g., the impact moment in a punch). We present an algorithm that processes the original joint angle data to produce a new motion in which the end-effector error is reduced to zero at keyframes. The new motion should not be too much different from the original motion. We formulated the problem as a constrained minimization problem so that the characteristics of the original joint angle data is optimally preserved during the enhancement steps. The algorithm was applied to several examples such as boxing, kicking, and catching motions. Experiments prove that our algorithm is a valuable tool to improve captured motion especially when the end-effector trajectory contains a special goal.