TrackStudio: An Integrated Toolkit for Markerless Tracking
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866911275840176128 |
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| author | Dimitrov, Hristo Dominijanni, Giulia Pavalkyte, Viktorija Makin, Tamar R. |
| author_facet | Dimitrov, Hristo Dominijanni, Giulia Pavalkyte, Viktorija Makin, Tamar R. |
| contents | Markerless motion tracking has advanced rapidly in the past 10 years and currently offers powerful opportunities for behavioural, clinical, and biomechanical research. While several specialised toolkits provide high performance for specific tasks, using existing tools still requires substantial technical expertise. There remains a gap in accessible, integrated solutions that deliver sufficient tracking for non-experts across diverse settings.
TrackStudio was developed to address this gap by combining established open-source tools into a single, modular, GUI-based pipeline that works out of the box. It provides automatic 2D and 3D tracking, calibration, preprocessing, feature extraction, and visualisation without requiring any programming skills. We supply a user guide with practical advice for video acquisition, synchronisation, and setup, alongside documentation of common pitfalls and how to avoid them.
To validate the toolkit, we tested its performance across three environments using either low-cost webcams or high-resolution cameras, including challenging conditions for body position, lightning, and space and obstructions. Across 76 participants, average inter-frame correlations exceeded 0.98 and average triangulation errors remained low (<13.6mm for hand tracking), demonstrating stable and consistent tracking. We further show that the same pipeline can be extended beyond hand tracking to other body and face regions. TrackStudio provides a practical, accessible route into markerless tracking for researchers or laypeople who need reliable performance without specialist expertise. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_07624 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | TrackStudio: An Integrated Toolkit for Markerless Tracking Dimitrov, Hristo Dominijanni, Giulia Pavalkyte, Viktorija Makin, Tamar R. Computer Vision and Pattern Recognition Quantitative Methods Markerless motion tracking has advanced rapidly in the past 10 years and currently offers powerful opportunities for behavioural, clinical, and biomechanical research. While several specialised toolkits provide high performance for specific tasks, using existing tools still requires substantial technical expertise. There remains a gap in accessible, integrated solutions that deliver sufficient tracking for non-experts across diverse settings. TrackStudio was developed to address this gap by combining established open-source tools into a single, modular, GUI-based pipeline that works out of the box. It provides automatic 2D and 3D tracking, calibration, preprocessing, feature extraction, and visualisation without requiring any programming skills. We supply a user guide with practical advice for video acquisition, synchronisation, and setup, alongside documentation of common pitfalls and how to avoid them. To validate the toolkit, we tested its performance across three environments using either low-cost webcams or high-resolution cameras, including challenging conditions for body position, lightning, and space and obstructions. Across 76 participants, average inter-frame correlations exceeded 0.98 and average triangulation errors remained low (<13.6mm for hand tracking), demonstrating stable and consistent tracking. We further show that the same pipeline can be extended beyond hand tracking to other body and face regions. TrackStudio provides a practical, accessible route into markerless tracking for researchers or laypeople who need reliable performance without specialist expertise. |
| title | TrackStudio: An Integrated Toolkit for Markerless Tracking |
| topic | Computer Vision and Pattern Recognition Quantitative Methods |
| url | https://arxiv.org/abs/2511.07624 |