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POLIMOD Pipeline: tutorial: step-by-step tutorial: Motion Capture, Visualization & Data Analysis for gesture studies

Abstract : This open-access tutorial describes step-by-step how to use motion capture for gesture studies. We propose a pipeline to collect, visualize, annotate and analyze motion capture (mocap) data for gesture studies. A pipeline is "an implementation of a workflow specification. The term comes from computing, where it means a set of serial processes, with the output of one process being the input of the subsequent process. A production pipeline is not generally perfectly serial because real workflows usually have branches and iterative loops, but the idea is valid: A pipeline is the set of procedures that need to be taken in order to create and hand off deliverables" (Okun, 2010). The pipeline designed here presents two main parts and three subparts. The first part of the pipeline describes the data collection process, including the setup and its prerequisites, the protocol to follow and how to export data regarding the analysis. The second part is focusing on data analysis, describing the main steps of Data processing, Data analysis itself following different gesture descriptors, and Data visualization in order to understand complex or multidimensional gesture features. We design the pipeline using blocks connected with arrows. Each block is presenting a specific step using hardware or software. Arrows represent the flow of data between each block and the 3-letter acronyms attached refer to the data file format.
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Contributor : Jean-François Jégo <>
Submitted on : Tuesday, December 11, 2018 - 12:10:52 AM
Last modification on : Tuesday, May 5, 2020 - 11:50:13 AM
Long-term archiving on: : Tuesday, March 12, 2019 - 12:40:43 PM


POLIMOD 2017-18 - PIPELINE Tut...
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  • HAL Id : hal-01950615, version 1


Dominique Boutet, Jean-François Jégo, Vincent Meyrueis. POLIMOD Pipeline: tutorial: step-by-step tutorial: Motion Capture, Visualization & Data Analysis for gesture studies. [Technical Report] Université de Rouen, Université Paris 8, Moscow State Linguistic University. 2018. ⟨hal-01950615⟩



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