Editing Motion capture (section)

==Methods and systems==
[[File:Kistler plates.jpg|thumb|right|Reflective markers attached to skin to identify body landmarks and the 3D motion of body segments]]
[[File:Silhouette tracking.PNG|thumb|Silhouette tracking]]

Motion tracking or motion capture started as a photogrammetric analysis tool in biomechanics research in the 1970s and 1980s, and expanded into education, training, sports and recently [[computer animation]] for [[television]], [[film|cinema]], and [[video game]]s as the technology matured. Since the 20th century, the performer has to wear markers near each joint to identify the motion by the positions or angles between the markers. Acoustic, inertial, [[LED]], magnetic or reflective markers, or combinations of any of these, are tracked, optimally at least two times the frequency rate of the desired motion. The resolution of the system is important in both the spatial resolution and temporal resolution as motion blur causes almost the same problems as low resolution. Since the beginning of the 21st century - and because of the rapid growth of technology - new methods have been developed. Most modern systems can extract the silhouette of the performer from the background. Afterwards all joint angles are calculated by fitting in a mathematical model into the silhouette. For movements you can not see a change of the silhouette, there are hybrid systems available that can do both (marker and silhouette), but with less marker.{{citation needed|date=January 2019}} In robotics, some motion capture systems are based on [[simultaneous localization and mapping]].<ref>Sturm, Jürgen, et al. "[http://jsturm.de/publications/data/sturm12iros.pdf A benchmark for the evaluation of RGB-D SLAM systems]." Intelligent Robots and Systems (IROS), 2012 IEEE/RSJ International Conference on. IEEE, 2012.</ref>
{{Further|Left-hand–right-hand activity chart|Kinematics}}