AirCamRTM: Enhancing Vehicle Detection for Efficient Aerial Camera-Based Road Traffic Monitoring

Abstract

Efficient road traffic monitoring is playing a fundamental role in successfully resolving traffic congestion in cities. Unmanned Aerial Vehicles (UAVs) or drones equipped with cameras are an attractive proposition to provide flexible and infrastructure-free traffic monitoring. However, real-time traffic monitoring from UAV imagery poses several challenges, due to the large image sizes and presence of non relevant targets. In this paper, we propose the AirCam-RTM framework that combines road segmentation and vehicle detection to focus only on relevant vehicles, which as a result, improves the monitoring performance by approximately 2x and provides approximately 18% accuracy improvement. Furthermore, through a real experimental setup we qualitatively evaluate the performance of the proposed approach, and also demonstrate how it can be used for real-time traffic monitoring and management using UAVs.