Research Article
A Video Surveillance Network for Airport Ground Moving Targets
@INPROCEEDINGS{10.1007/978-3-030-64002-6_15, author={Xiang Zhang and Yi Qiao}, title={A Video Surveillance Network for Airport Ground Moving Targets}, proceedings={Mobile Networks and Management. 10th EAI International Conference, MONAMI 2020, Chiba, Japan, November 10--12, 2020, Proceedings}, proceedings_a={MONAMI}, year={2020}, month={12}, keywords={Airport ground surveillance Moving object detection}, doi={10.1007/978-3-030-64002-6_15} }- Xiang Zhang
Yi Qiao
Year: 2020
A Video Surveillance Network for Airport Ground Moving Targets
MONAMI
Springer
DOI: 10.1007/978-3-030-64002-6_15
Abstract
In this paper we describe an airport ground movement surveillance network. Airport ground videos are captured by multiple cameras, and than transmitted to the airport control center based on the optical fiber network. On the high-performance servers in the control center, various intelligent applications process video data, visualize the processing results and provide them to the air traffic controllers as a reference for airport management. Moving object detection is the foundation of many video based intelligent applications in airport surveillance. We propose detecting the moving objects in the airport ground by the use of the prior knowledge, that is, the airport ground made of cement has a gray-white color distribution. Based on this fact, firstly we use a dual-mode Gaussian distribution to fit the color distribution of the ground. Next, based on the fitted distribution we build a prior model, where pixels near the class boundary are more likely to be classified as the foreground. Finally, the prior model is used to detect moving targets within a Bayesian classification framework. Experiments are conducted on the AGVS benchmark and the results demonstrate the effectiveness of the proposed moving object detection algorithm.
