Skinning is the name given to the technique whereby a polygon skin is derived from an underlying articulating skeleton. We reverse this process, starting with a collection of points positioned on the surface of a character and then generating an underlying skeleton using a constrained optimisation approach. We call this inverse skinning. The surface data is collected from an optical motion capture system, but could also be derived from other capture processes. The technique presented is tolerant to erroneous data and is suitable for streaming datasets due to the per- frame nature of the process.

A sheet feeder for feeding sheets accurately in correct orientation, especially to a press for blanking pieces from the sheet, has an intermittent sheet-advancing action in which not only the movement of the sheet, but also its orientation with respect to the path of travel and its transverse position, are determined solely by pusher dogs without any need for side guides. The pusher dogs fit in recesses in the rear edge of the sheet in such a way that the transverse position of the sheet is determined accurately by an abrupt discontinuity of the recess or recesses engaging a pusher dog.

In this paper we present a technique that enhances an inverse kinematics (IK) solver such that when the results are applied to a computer character we can generate a level of individualisation tailored to both the character and the environment, e.g. a walking motion can become ‘stiffer’ or can be turned into a limping motion. Since the technique is based on an IK solver, we also have the desirable effect of solving retargetting issues when mapping motion data between characters. As the individualisation aspect of our technique is very tightly coupled with the inverse kinematics solver, we can achieve both the individualisation and retargetting of characters in real time.