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<p>Motion capture technology has applications in a wide range of fields, including entertainment, medicine, and sports, to name a few. But what if the measurements these systems were based on were rooted in social practices and biased assumptions, leading to errors that become ingrained over time? This question is at the heart of&nbsp;<a href="https://arxiv.org/abs/2401.10877">new research</a>&nbsp;co-authored by&nbsp;<a href="https://datascience.virginia.edu/people/mona-sloane">Mona Sloane</a>, an assistant professor of data science and media studies at the University of Virginia.&nbsp;</p>

Cornell schoolUnited statesHauke sandhausEmma harveyEmanuel mossMona sloaneAbigal jacobsUniversity school of data scienceUniversity of michiganAssociation of computing machinerySloane labUniversity of virginiaValidation in motion capture technologyUs airDepartment of mediaCornell school of information science