The client is a sports technology company that works with motion capture footage of athletic drills. Its videos show solo hurdle drills: cooldown walks, bounce jumps, lateral steps, lateral jumps, high knee runs, and multi-segment hurdle course runs. The company uses labeled motion data to train AI and machine learning models for motion analysis and animation.
The client needed motion capture video labeled in enough detail for a model to tell similar athletic movements apart. Each video file required 18 to 32 rows of structured data, 10 to 23 distinct labeled actions, and 2 to 4 strong pose markers that anchor the model’s recognition of key athletic positions.
Scene complexity varied from file to file. Some videos showed a single athlete and others showed two, which meant two or four performance characters on screen. The labels also had to load into the client’s machine learning and animation pipelines without reprocessing.
The client brought in HitechDigital to label 1,100 hurdle drill videos with consistent actions and pose markers, and to run quality checks precise enough for high-fidelity movement replication.
HitechDigital built a four-stage pipeline of labeling, QC, audit, and dispatch that delivered 31,000 action labels across 1,100 hurdle drill video files at 98% accuracy. Every dispatched file met the client’s structural and formatting requirements, and the client accepted 100% of the records it reviewed.
AI-assisted label standardization tools, with per-file tracking and ETA dashboards.
