This project investigates in much more detail the human anatomy and dynamics to further progress in replicating human articulation capabilities. To overcome long-standing imaging limitations, the project follows a data-driven approach, in which sampled dynamic motion data is used to infer unknown parameters such as soft-tissue geometry and behavior. The project is cross-disciplinary and driven by specific problems in orthopaedics and human character animation, although its focus is fundamentally on computational and automated analysis tools. The research plan develops computational tools for capturing robustly and accurately dynamic skeletal motion from medical images, for inferring biological shape and behavior from dynamic motion information, and for representing and calculating with these data. The education effort is naturally integrated with the research work, and includes recruiting and training graduate, undergraduate, and high-school students into multi-disciplinary work, through a modeling and simulation approach to teaching computer graphics. The outcome of the project is a set of human-anatomy based (i.e., humanoid) models of articulations that impacts orthopaedists' understanding of articulation injury and disease, leads to improved diagnosis and medical treatment, and improves the realism of digital character animation. The broad impact of the project includes applications in biology, bioengineering, ergonomics, evolutionary biology and robotics. Results of this project, including software, data, and publications, are publicly available through the project web site, http://vis.cs.pitt.edu/marai_nsf_career
