  This paper presents Master of Puppets (MOP), an animation-by-demonstration
framework that allows users to control the motion of virtual characters
(puppets) in real time. In the first step, the user is asked to perform the
necessary actions that correspond to the character's motions. The user's
actions are recorded, and a hidden Markov model (HMM) is used to learn the
temporal profile of the actions. During the runtime of the framework, the user
controls the motions of the virtual character based on the specified
activities. The advantage of the MOP framework is that it recognizes and
follows the progress of the user's actions in real time. Based on the forward
algorithm, the method predicts the evolution of the user's actions, which
corresponds to the evolution of the character's motion. This method treats
characters as puppets that can perform only one motion at a time. This means
that combinations of motion segments (motion synthesis), as well as the
interpolation of individual motion sequences, are not provided as
functionalities. By implementing the framework and presenting several computer
puppetry scenarios, its efficiency and flexibility in animating virtual
characters is demonstrated.
