Motion Capture Capture de mouvement

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Definition

Motion capture A recording technique that locates the position of living beings or objects within space, making it possible to model their movements digitally and create 3D graphic representations in a virtual environment.

Cite: “Motion capture”, Performascope: Interdisciplinary Lexicon of Performance and Research-Creation, Grenoble: Université Grenoble Alpes, 2021, [online]: http://performascope.univ-grenoble-alpes.fr/en/detail/177599

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Created : 2021-06-09.

Last modified : 2022-06-29.

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« Motion Capture (MoCap) describes the process of digitally recording movement in 360 degrees and translating that movement onto a model in projected or screen-based 3D space. While it borrows from traditional filmmaking, its major distinction is that it does not record what would be traditionally referred to as the framed moving image (the translation of the 3D to the 2D) but more accurately records an accurate impression of plotted movement in 3D space that can be transferred to a screenbased 3D impression. There are several modes of MoCap, with device types best grouped into two distinct forms: optical (passive, active and marker less) and non-optical (magnetic, inertial and mechanical). A passive optical MoCap system is the type most often deployed in the commercial animation and filmmaking sector. It allows for several objects to be captured at once and provides the greatest accuracy.2 While MoCap is used extensively in military and biomedical applications, it is the terminology of creative applications that are defined here. In filmmaking it refers to recording actions of human actors, and using that information to animate digital character models in 3D animations to be used in computer generated imagery (CGI). »

Matt Delbridge, Motion Capture in Performance. An introduction, Hampshire : Palgrave Macmillan, 2015, p.26

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Jacky C. P. Chan, Howard Leung, Jeff K.T Tang, Taku Komura, « A Virtual Reality Dance Training System Using Motion Capture Technology », IEEE Transactions on Learning Technologies, 4, 2, 2011, pp. 187-195

Lionel Reveret, « Mesures et modèles pour la capture de mouvement. Traitement du signal et de l’image », [Habilitation à Diriger des Recherches], Institut National Polytechnique de Grenoble, 2014, [en ligne] : https://tel.archives-ouvertes.fr/tel-01064134 (09/06/2021)

Leonid Sigal, Alexandru O. Balan, and Michael J. Black, « Humaneva : Synchronized video and motion capture dataset and baseline algorithm for evaluation of articulated human motion », International Journal of Computer Vision, 1-2, 87, 2010, pp.4-27, [en ligne] : https://link.springer.com/article/10.1007/s11263-009-0273-6 (09/06/2021)