Optical Flow-Enhanced Thermal UAV Detection Under Camera Ego-Motion for Real-Time Tactical C-UAV
Year: 2026
Type: article
Abstract: Thermal UAV detection from mobile platforms is difficult because camera ego-motion corrupts the motion cues needed to detect small airborne targets. We present an optical flow enhanced YOLO detector that fuses thermal appearance with dense horizontal and vertical flow channels through a custom OpticalFlowConv stem. On the Anti-UAV thermal benchmark (233,667 frames across 205 sequences), using a sequential per-sequence split that preserves temporal order, the proposed detector reaches 35.8% mAP50 and 21.9% mAP50-95, outperforming a single-frame YOLO11 baseline by 11.3 mAP50 points and a frame-differencing baseline by 9.1 points. These results support motion-enhanced thermal detection as a practical sensing component for mobile tactical C-UAV systems under significant camera motion.
Institution: University of Waterloo
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7218152764