A group of novel approaches and a toolkit for motion capture data reusing

Abstract

Now more and more motion capture (MoCap) systems are used to acquire realistic and highly detailed motion data which are widely used for producing animations of human-like characters in a variety of applications, such as simulations, video games and animation films. And recently large MoCap databases are available. As a kind of emerging multimedia data, 3D human motion has its own specific data form and standard format. But to the best of our knowledge, only a few approaches have been explored for 3D MoCap data feature representation and reusing. This paper proposes a group of novel approaches for posture feature representation, motion sequence segmentation, key-frame extraction and content-based motion retrieval, which are all very important for MoCap data reusing and benefit to the efficient animation production. To validate these approaches, we set up a MoCap database and implemented a prototype toolkit. The experiments show that the proposed algorithms could achieve the approvable results.