Moving vehicle detection with convolutional networks in UAV videos

Moving vehicle detection from unmanned aerial vehicles (UAV) is becoming an increasingly important research topic in traffic monitoring, surveillance and military applications. Owing to the low-quality of UAV videos and the movement of the platform, vehicle detection is a challenging task. Existing algorithms that are generally designed for stationary cameras are ineffectively under this situation. This paper proposes an accurate moving vehicle detector. Significant contributions include a real-time, high detection rate approach for motion detection with image registration, candidate targets detection and vehicle screening using convolutional neural network. Experiments on a variety of data sets show the successful detection of moving vehicle under varying conditions. Currently the detection rate for vehicle is up to 90% and the average false alarm rate is less than 10%.