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Seeeeeyo merged 1 commit into from
Aug 3, 2026
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work that used this software #42

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Expand Up @@ -194,7 +194,7 @@ OpenCap Visualizer supports high-throughput biomechanics workflows where manual,

# Research Impact Statement

OpenCap Visualizer is integrated into the OpenCap [@opencap] processing pipeline and serves as the default visualization tool for OpenCap Monocular [@opencap-monocular]. The Python package is published on PyPI ([https://pypi.org/project/opencap-visualizer](https://pypi.org/project/opencap-visualizer)) and has been used by our group to run a parameter optimization across several hundred trials to visualize the resulting motions from OpenCap Monocular, with both the qualitative figures and the supplementary motion videos in [@opencap-monocular] generated directly with the tool. The browser viewer has further supported peer collaboration on OpenCap projects through shareable URLs. The codebase is released open-source under the Apache License 2.0 on GitHub with public issue tracking, automated PyPI releases, and worked examples in the repository. Near-term uptake is anticipated by groups working with markerless motion capture, real-time biofeedback, and large-scale field studies, where the absence of a scriptable, browser-based visualizer has been a recurring bottleneck.
OpenCap Visualizer is integrated into the OpenCap [@opencap] processing pipeline and serves as the default visualization tool for OpenCap Monocular [@opencap-monocular]. The Python package is published on PyPI ([https://pypi.org/project/opencap-visualizer](https://pypi.org/project/opencap-visualizer)) and has been used by our group to run a parameter optimization across several hundred trials to visualize the resulting motions from OpenCap Monocular, with both the qualitative figures and the supplementary motion videos in [@opencap-monocular] generated directly with the tool. It has also been used to develop and illustrate a foundation model of gait kinematics [@Magruder2026]. The browser viewer has further supported peer collaboration on OpenCap projects through shareable URLs. The codebase is released open-source under the Apache License 2.0 on GitHub with public issue tracking, automated PyPI releases, and worked examples in the repository. Near-term uptake is anticipated by groups working with markerless motion capture, real-time biofeedback, and large-scale field studies, where the absence of a scriptable, browser-based visualizer has been a recurring bottleneck.


# AI Usage Disclosure
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