TATraffic Analyzer

WIUT Hackathon 2026 · Computer Vision track

Traffic events from a fixed road camera, as time segments you can click.

We detect and track every road user, align a hand-drawn map of the junction to each clip, and turn trajectories into events such as jaywalking, red-light running and congestion.

sample clips analysed
4
event classes detected
7 / 14
camera resolution and fps
4K · 29.97
scene-map alignment residual
< 0.5 px

How it works

One learned component, everything after it deterministic. Read the full approach.

  1. MP4 video
    4K, 29.97 fps, fixed camera
  2. Frame samplingRule-based
    Decode once, analyse a subset of frames
  3. YOLO detectorLearned
    Fine-tuned, 8 classes incl. red/green signal heads
  4. ByteTrackRule-based
    Track ids and trajectories per road user
  5. Scene alignmentRule-based
    SIFT + RANSAC homography maps scene.json onto the clip
  6. Event rulesRule-based
    Per-class geometry and timing rules on tracks and zones
  7. Segment mergingRule-based
    Merge fragments, drop blips, no same-class overlap
  8. Events
    [start_sec, end_sec, label]

Blue border = learned component. Everything else is deterministic code whose thresholds are listed below.

Sample videos

Playback, event timeline and EDA for every clip the organizers gave us.