[Vision AI] Hierarchical Object Detection: YOLOv3 Vehicle ROI, YOLOv5 Plate Detector & CSRT Tracking (#3)
· 2 min read
📌 Key Takeaways (TL;DR)
- Problem: Searching for tiny plates (30x15 pixels) across the raw 640x480 frame generates massive false positives from roadside signs and drops inference speed below 10 FPS.
- Solution: Designed a two-stage hierarchical architecture: broad vehicle detection (YOLOv3-tiny) crops the vehicle ROI, within which a fine-tuned YOLOv5 (lp_det.pt, conf=0.6) locates the license plate. Integrated OpenCV CSRT correlation filter tracking with a 15-frame redetection interval.
- Result: Eliminated 98% of background false positives and slashed GPU overhead by 80%, sustaining real-time 50+ FPS continuous tracking.