CCE Theses and Dissertations

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Date of Award


Document Type

Dissertation - NSU Access Only

Degree Name

Doctor of Philosophy in Computer Science (CISD)


Graduate School of Computer and Information Sciences


Michael Laszlo

Committee Member

Sumitra Mukherjee

Committee Member

Martin Barrett


Balancing Human Algorithm, Featherstone, Human Motion, Posture Prediction, Procedural Animation, Real-time Graphics


Procedural human motion generation is still an open area of research. Most research into procedural human motion focus on two problem areas: the realism of the generated motion and the computation time required to generate the motion. Realism is a problem because humans are very adept at spotting the subtle nuances of human motion and so the computer generated motion tends to look mechanical. Computation time is a problem because the complexity of the motion generation algorithms results in lengthy processing times for greater levels of realism.

The balancing human problem poses the question of how to procedurally generate, in real-time, realistic standing poses of an articulated human body. This report presents the balancing human algorithm that addresses both concerns: realism and computation time. Realism was addressed by integrating two existing algorithms. One algorithm addressed the physics of the human motion and the second addressed the prediction of the next pose in the animation sequence. Computation time was addressed by identifying techniques to simplify or constrain the algorithms so that the real-time goal can be met.

The research methodology involved three tasks: developing and implementing the balancing human algorithm, devising a real-time simulation graphics engine, and then evaluating the algorithm with the engine. An object-oriented approach was used to model the balancing human as an articulated body consisting of systems of rigid-bodies connected together with joints. The attributes and operations of the object-oriented model were derived from existing published algorithms.

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