Moving vehicle detection with convolutional networks in UAV videos

• Published in: 2016 2nd International Conference on Control, Automation and Robotics (ICCAR) pp. 225 - 229
• Main Authors: Youyang Qu, Liang Jiang, Xinping Guo
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.04.2016
• Subjects: convolutional neural network; Image registration; moving vehicle detection; Neural networks; Training; unmanned aerial vehicle (UAV); Unmanned aerial vehicles; Vehicle detection; Videos
• ISBN: 9781467398589; 1467398586
• DOI: 10.1109/ICCAR.2016.7486730

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%.