Handling Motion Processing Constraints for Articulated Figure Animation

The animation of articulated models such as human figures remains a major challenge because of the many degrees of freedom involved and the complex structure of the models. A particular challenge is to find ways to generate new movement from existing movement sequences produced by animating or motion capture. Techniques from the image and signal processing domain can be applied to motion sequences. We have successfully applied motion multiresolution filtering, multitarget motion interpolation and waveshaping simultaneously to many or all degrees of freedom of an articulated figure. Thus we can edit, modify and blend existing motions in ways that would be difficult or impossible to accomplish otherwise. These motion transforms result in interesting new movement sequences but may introduce constraint violations. The constraint violation problem is inherent to the motion transform techniques and cannot be avoided. In this thesis, we first show how to generally reduce the chance and degree of constraint violations by offsetting motion data and applying consistent dynamic timewarping before motion transforms. One way is provided to let the animator specify constraints, and the system checks the constraints and adjusts the constraint violations in a smooth manner before the new motion is presented to the animator. Most geometric constraint violations can be handled successfully at interactive speeds with our system. We also provide some tools for the animator to modify the new motion at a relatively low level, thus giving the animator more control over constraint violation adjustment; therefore these tools can be used to handle constraints which are hard to specify in the above system. -----Dedicated to My Parents