Reconstructing individual hand models from motion capture data

Reconstructing Motion Capture Data for Human Crowd Study

Reconstruction is a key step of the motion capture process. The quality of motion data first results from the quality of raw data. However, it also depends on the motion reconstruction step, especially when raw data suffer markers losses or noise due, for example, to challenging conditions of capture. Labeling is a final and crucial data reconstruction step that enables practical use of motion ...

Articulated Motion Analysis from Motion Capture Data

We present computational methods to extract and model different joints of a generic subject, in an automatic way. The input for our methods is simply a set of trajectories of 3D points, obtained from a motion capture system (MOCAP). Due to the piecewise rigidity of the skeleton, these trajectories belong to different subspaces (of the space of all possible trajectories). We use this knowledge t...

Expressive Facial Gestures From Motion Capture Data

Human facial gestures often exhibit such natural stochastic variations as how often the eyes blink, how often the eyebrows and the nose twitch, and how the head moves while speaking. The stochastic movements of facial features are key ingredients for generating convincing facial expressions. Although such small variations have been simulated using noise functions in many graphics applications, ...

Character Animation from Motion Capture Data

An automated time and hand motion analysis based on planar motion capture extended to a virtual environment

In the context of industrial engineering, the predetermined time systems (PTS) play an important role in workplaces because inefficiencies are found in assembly processes that require manual manipulations. In this study, an approach is proposed with the aim to analyze time and motions in a manual process using a capture motion system embedded to a virtual environment. Capture motion system trac...