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Surrounding Vehicle Tracking System
YOLOv8-based system for detecting and tracking surrounding vehicles and estimating their speed from a camera feed.
PythonYOLOv8 (Ultralytics)OpenCVJupyter Notebook (exploration)`speed_estimation.py` (inference pipeline)
⚡ Estimating real-world speed from 2D pixel displacement witho…⚡ Handling occlusion and ID switching in multi-vehicle trackin…⚡ Balancing detection frequency and speed smoothing to produce…
Portfolio Highlights
- →Implemented a YOLOv8-based surrounding vehicle detection and speed estimation pipeline using frame-to-frame displacement tracking.
Snapshot
- Period: 2025 (pushed to GitHub: May 2026)
- Source: `aspire7:D:\ML\surrounding-vehicle-tracking-system` · `github.com/josegibson/surrounding-vehicle-tracking-system`
- Domain: Computer vision, object tracking, speed estimation
- Status: Research prototype
Stack
- Python
- YOLOv8 (Ultralytics)
- OpenCV
- Jupyter Notebook (exploration)
- `speed_estimation.py` (inference pipeline)
What I Built
- Vehicle detection and tracking pipeline using YOLOv8.
- Speed estimation logic derived from object displacement across frames with known camera parameters or approximations.
- Notebook documenting the methodology and results (`how_to_estimate_vehicle_speed_with_computer_vision.ipynb`).