Moving vehicle detection with convolutional networks in UAV videos
Youyang Qu, Jiang Liang, Xinping Guo · 2016
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%.