Learning Human Pose and Motion Models for Animation
published: Feb. 25, 2007, recorded: June 2006, views: 849
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Computer animation is an extraordinarily labor-intensive process; obtaining high-quality motion models could make the process faster and easier. I will describe methods for learning models of human poses and motion from motion capture data. I will begin with a pose model based on the Gaussian Process Latent Variable Model (GPLVM), and the application of this model to Inverse Kinematics posing. I will then describe the Gaussian Process Dynamical Model (GPDM) for modeling motion dynamics. I may also mention a few other extensions to the GPLVM for modeling motion data. I will discuss the properties of these models (both good and bad) and potential directions for future work.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !