1. A computing system, comprising: a camera input subsystem to receive depth-camera recordings; one or more memory devices holding instructions to retrain a general-purpose body part tracker; one or more processors configured to execute the instructions to: receive via the camera input subsystem, a set of different instances of scenario data, each instance of scenario data including one or more depth images representing a depth-camera recording of a human training-subject performing an action specific to a particular scenario; iterate 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; identify 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 associate 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.