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Pose estimation is a systems problem, not a model bake-off

· 6 min read
Sai Prudhvi Neelakantam
Senior Consultant, Data Engineering & AI at Evidi

Point a camera at a person, draw a skeleton, call it live. That demo survives a recorded clip and dies on a messy stream: variable lighting, dropped frames, busy backgrounds, and users who feel 80 ms of lag even if they cannot name it.

Accuracy without a calm loop is a lab number. End-to-end time to a stable overlay is what people experience. Treat capture, inference, and render as three jobs that can each fail independently.

Object detection overlay example from Azure AI Vision image analysis

Figure 1. Vision pipelines succeed when the frame path stays explicit: capture, analyze, present. Pose work has the same loop, just with landmarks instead of boxes. Source: Microsoft Learn: image analysis overview.