Behavioural capture stack
What is read from the video?
- Inputs
- Any modern video: venue AV, GoPro, iPhone, webcam. No wearables.
- Computation
- Frames are sampled, not read one by one, so compute stays bounded on a long session. A 2 minute clip runs at 12 frames a second, a 10 minute clip at 2, an hour at one frame per 4 seconds. What runs on each sampled frame depends on the read. A room read, which is what a single event clip gets by default, runs a tiled face detector over the frame and keeps a count and a coarse per-face orientation. It does not build a facial mesh, and it derives no action units: at the 25 to 35 pixel face sizes a room produces, a fine-grained facial read would be noise. A single-subject read is the path that runs MediaPipe FaceMesh at 468 landmarks per face and derives action units from it. Face embeddings are not stored on either path. Only the scoring numbers survive the pass.
- Output
- On a room read, one record per sampled frame holding the room count, how many of those faces were large enough to score, and the fraction oriented toward the stage. Oriented toward the stage is a geometric proxy off the detector keypoints, not a gaze measurement, and no row is ever tied to a person. On a single-subject read, one record per sampled frame carrying the action-unit strengths and head pose for the one tracked face.