δ-ATP: Towards Fast and Reliable Aerial Traffic Patrol
Year: 2025
Type: conference-paper
Abstract: In this work, we present our efforts to develop δ-ATP, a working system for fast and reliable traffic patrol using drones in the sky. Compared to the state-of-art approaches, δ-ATP improves accuracy and responsiveness in detecting speeding incidents by focusing only on essential "delta" (δ) information - regions of interest (say, roads) and key frames needed for speed estimation. We have implemented and evaluated δ-ATP in real-world experiments, successfully detecting all the speeding vehicles and outperforming all other approaches with a higher accuracy for real-time traffic enforcement. The datasets collected in our field test are available at [7].
Authors: Jiaxin Du, Chunyi Peng
Institution: Purdue University West Lafayette
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4414760463