MarkerLess Motion Capture: ML-MoCap, a low-cost modular multi-camera setup

Jinne E. Geelen, Mariana P. Branco, Nick F. Ramsey, Frans C.T. van der Helm, Winfred Mugge, Alfred C. Schouten

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

6 Citations (Scopus)
100 Downloads (Pure)

Abstract

Motion capture systems are extensively used to track human movement to study healthy and pathological movements, allowing for objective diagnosis and effective therapy of conditions that affect our motor system. Current motion capture systems typically require marker placements which is cumbersome and can lead to contrived movements.Here, we describe and evaluate our developed markerless and modular multi-camera motion capture system to record human movements in 3D. The system consists of several interconnected single-board microcomputers, each coupled to a camera (i.e., the camera modules), and one additional microcomputer, which acts as the controller. The system allows for integration with upcoming machine-learning techniques, such as DeepLabCut and AniPose. These tools convert the video frames into virtual marker trajectories and provide input for further biomechanical analysis.The system obtains a frame rate of 40 Hz with a sub-millisecond synchronization between the camera modules. We evaluated the system by recording index finger movement using six camera modules. The recordings were converted via trajectories of the bony segments into finger joint angles. The retrieved finger joint angles were compared to a marker-based system resulting in a root-mean-square error of 7.5 degrees difference for a full range metacarpophalangeal joint motion.Our system allows for out-of-the-lab motion capture studies while eliminating the need for reflective markers. The setup is modular by design, enabling various configurations for both coarse and fine movement studies, allowing for machine learning integration to automatically label the data. Although we compared our system for a small movement, this method can also be extended to full-body experiments in larger volumes.

Original languageEnglish
Title of host publication2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
Pages4859-4862
Number of pages4
ISBN (Electronic)978-1-7281-1179-7
DOIs
Publication statusPublished - 9 Dec 2021
Externally publishedYes
Event43rd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2021: Changing Global Health Care in the Twenty-First Century - Virtual
Duration: 1 Nov 20215 Nov 2021
Conference number: 43

Conference

Conference43rd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2021
Abbreviated titleEMBC
Period1/11/215/11/21

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