## 2 Background and Related Work
### Motion Recordings  
Motion Capture (MoCap) refers to a wearable human motion recording modality that acquires 3D measurements of human motion, with a variety of technologies having been used for its implementation [22]. The output of MoCap is a set of series of 3D locations. Each series records the 3D locations of a physical point of the body. Optical, or Computer Vision systems estimate the same information through 2D measurements in images or video.  
The most widely used approach is optical MoCap and is achieved by the placement of markers on the moving body [23]. Off the shelf products include OptiTrack ([[https://optitrack.com](https://optitrack.com)]([https://optitrack.com](https://optitrack.com))) and Vicon ([[https://www.vicon.com/](https://www.vicon.com/)]([https://www.vicon.com/](https://www.vicon.com/))). The Inertial MoCap approach is based on Inertial Measurement Units (IMUs) to record motion, woven within an elastic suit [24]. Off-the-shelf products include NANSENSE Biomed MoCap System ([[https://www.nansense.com/](https://www.nansense.com/)]([https://www.nansense.com/](https://www.nansense.com/))) and Rokoko ([[https://www.rokoko.com](https://www.rokoko.com)]([https://www.rokoko.com](https://www.rokoko.com))). The topological mapping of markers follows that of the human skeleton. Marker-less optical systems infer 3D motion from conventional videos, using machine learning approaches that identify the human body and recognize its posture given appropriate training data [25; 26].  
Motion recordings vary in accuracy and precision depending on the MoCap acquisition technology [27]. In general, optical MoCap is more accurate than inertial MoCap; however, research on inertial tracking is active and producing frequent advances, tailored for the human body [28]. The least accuracy is provided by marker-less optical systems, due to a lack of direct 3D measurements. Post-processing of the recording is often required, a task that requires human supervision and interaction, and is facilitated by a range of visual tools, such as MotionBuilder ([[https://www.autodesk.com/products/motionbuilder/overview](https://www.autodesk.com/products/motionbuilder/overview)]([https://www.autodesk.com/products/motionbuilder/overview](https://www.autodesk.com/products/motionbuilder/overview))), Blender ([[https://www.blender.org/](https://www.blender.org/)]([https://www.blender.org/](https://www.blender.org/))), and Maya ([[https://de.rebusfarm.net/en/3d-software/maya-render-farm](https://de.rebusfarm.net/en/3d-software/maya-render-farm)]([https://de.rebusfarm.net/en/3d-software/maya-render-farm](https://de.rebusfarm.net/en/3d-software/maya-render-farm))), etc.  
In all cases, the topology of markers is known and employed in the organisation of measurements. When capturing motion, markers are purposefully placed in association with the actual skeletal joints, delimiting its rigid components (actual bones). In this way, the hierarchic structure of the human skeleton is accounted for in the representation of human motion. In facial MoCap the markers are placed in association with anatomical locations on the face, such as the mouth and eyebrows, which are controlled by facial muscles and determine the expression of facial gestures (facial expressions).