1. A method of retraining a general-purpose body-part tracker, the method comprising: receiving a set of different instances of scenario data, each instance of scenario data representing a human training-subject performing an action specific to a particular scenario; iterating over the set of different instances of scenario data with the general-purpose body-part tracker, the general-purpose body-part tracker previously trained using supervised machine learning to identify one or more general-purpose parameters to be used by the general-purpose body-part tracker to track a human subject; and identifying one or more special-purpose parameters to be selectively used to augment or replace the one or more general-purpose parameters if the general-purpose body-part tracker is used to track a human subject performing the action specific to the particular scenario; and associating the one or more special-purpose parameters with a scenario identifier that identifies the particular scenario for which the special-purpose parameters are to be selectively used by the general-purpose body-part tracker to track a human subject.