running 0.95🏃
pose🤸
tracked🎯
Pose sequence over time is classified into an action. Illustrative walkthrough.
What it does
A video-understanding system that recognises human actions over time, not just single frames — useful for safety and analytics on existing CCTV streams.
How it works
- Step 1. Body keypoints (pose) are extracted from each frame of the CCTV stream.
- Step 2. A temporal model reads the sequence of poses.
- Step 3. It classifies the action — walking, running, falling, fighting…
- Step 4. Critical actions like a fall can trigger an immediate alert.
Where it's used
- Elderly fall detection
- Sports analytics
- Workplace safety
- Behaviour analytics
Tech stack
Build something like this
This project is part of our computer vision development and a fixed-price computer vision pilot. Tell us your use case and we will reply within one business day with a first step, a price and a date.
Architecture
How the pieces fit
- 01CCTV streamlive video
- 02Pose estimationkeypoints per person per frame
- 03Temporal modelreads the pose sequence
- 04Action labelwalk · run · fall → alert
InputProcessingOutput
Want something like Human Action Recognition?
Tell us your use case — we'll scope a build that fits.