Adaptive Animation of Human Motion for E-Learning Applications

Abstract

Human motion animation has been one of the major research topics in the field of computer graphics for decades. Techniques developed in this area help present human motions in various applications. This is crucial for enhancing the realism as well as promoting the user interest in the applications. To carry this merit to e-learning applications, we have developed efficient techniques for delivering human motion information over the Internet to collaborating e-learning users and revealing the motion information in the client machines with different rendering capability. Our method offers a mechanism to extract human motion data at various levels of detail (LoD). We also propose a set of importance factors to allow an e-learning system to determine the LoD of the human motion for rendering as well as transmission, according to the importance of the motion and the available network bandwidth. At the end of the paper, we demonstrate the effectiveness of the new method with some experimental results.