@conference {Mund2016,
	title = {Introducing LiDAR Point Cloud-based Object Classification for Safer Apron Operations},
	booktitle = {International Symposium on Enhanced Solutions for Aircraft and Vehicle Surveillance Applications},
	year = {2016},
	abstract = {Current procedures for conventional and remote airport ground control still rely on the direct (camera-) view. Despite further support by different Radar applications occasional shortcomings in the awareness of the responsible controllers may occur, particularly under adverse weather conditions, giving rise to capacity backlogs, incidents and accidents. As Laser scanners and computer vision algorithms have reached new performance levels in recent years, we proposed a novel concept for complete and independent airport apron surveillance based on LiDAR 3D point data. In this paper we extend our object detection/segmentation technique by addressing object classification in LiDAR 3D scans. We hereby enable LiDAR{\textquoteleft}s unique capability to classify non-cooperative objects by means of a single sensor and learned model knowledge. Our technique was able to classify and to estimate the poses of an Airbus A319-100 and a Boeing B737-700 parked on the airport apron. In the future we will enhance our classification technique to a wider range of objects including moving ground vehicles and pedestrians.},
	keywords = {- lidar, 3d point cloud, aircraft, airport ground surveillance, apron control, apron control rely on, classification, current legacy procedures for, laser scanning, pose estimation},
	url = {https://goo.gl/28Yoqh},
	author = {Mund, Johannes and Michel, Frank and Dieke-Meier, Franziska and Fricke, Hartmut and Meyer, Lothar and Carsten Rother}
}
@conference {Mund2015a,
	title = {Performance evaluation of LiDAR point clouds towards automated FOD detection on airport aprons},
	booktitle = {Proceedings of ATACCS 2015 - 5th International Conference on Application and Theory of Automation in Command and Control Systems},
	year = {2015},
	pages = {85{\textendash}94},
	abstract = {Both the current system of airport ground control and the continuous implementation efforts of A-SMGCS and Remote Tower concepts require complete and independent surveillance coverage in real-time. We believe that 3D point clouds generated by an actively scanning LiDAR system available at TU Dresden may satisfy these high standards. Nonetheless, the utilization of LiDAR sensing for airport ground surveillance purposes is extremely challenging due to the unique requirement profile in this domain. This is also the reason why existing solutions in other domains such as autonomous driving and robotics are not directly applicable for airport ground surveillance. In a first step, we developed point cloud object detection and segmentation techniques to present that new data comprehensively to the airport apron controller. In this paper, we focused on the timely detection of dislocated objects (foreign object debris, forgotten equipment etc.) as a serious cause to hazardous situations on airport movement areas. The results are promising for various reference targets. However, the detection of very small objects (e.g. socket wrench) requires more elaborate algorithms to take full advantage of the current LiDAR technology. In the future we will assess the strength of LiDAR-based surveillance in terms of the number of hazardous situations that could be avoided or safely managed by the apron controller.},
	keywords = {Airport surveillance, apron control, Apron management service, FOD, Foreign object debris, laser scanning, LiDAR, Object detection, Point cloud},
	isbn = {9781450335621},
	doi = {10.1145/2899361.2899370},
	author = {Mund, Johannes and Zouhar, Alexander and Meyer, Lothar and Fricke, Hartmut and Carsten Rother}
}
@conference {Mund2015,
	title = {Performance evaluation of LiDAR point clouds towards automated FOD detection on airport aprons},
	booktitle = {Proceedings of ATACCS 2015 - 5th International Conference on Application and Theory of Automation in Command and Control Systems},
	year = {2015},
	pages = {85{\textendash}94},
	abstract = {Both the current system of airport ground control and the continuous implementation efforts of A-SMGCS and Remote Tower concepts require complete and independent surveillance coverage in real-time. We believe that 3D point clouds generated by an actively scanning LiDAR system available at TU Dresden may satisfy these high standards. Nonetheless, the utilization of LiDAR sensing for airport ground surveillance purposes is extremely challenging due to the unique requirement profile in this domain. This is also the reason why existing solutions in other domains such as autonomous driving and robotics are not directly applicable for airport ground surveillance. In a first step, we developed point cloud object detection and segmentation techniques to present that new data comprehensively to the airport apron controller. In this paper, we focused on the timely detection of dislocated objects (foreign object debris, forgotten equipment etc.) as a serious cause to hazardous situations on airport movement areas. The results are promising for various reference targets. However, the detection of very small objects (e.g. socket wrench) requires more elaborate algorithms to take full advantage of the current LiDAR technology. In the future we will assess the strength of LiDAR-based surveillance in terms of the number of hazardous situations that could be avoided or safely managed by the apron controller.},
	keywords = {Airport surveillance, apron control, Apron management service, FOD, Foreign object debris, laser scanning, LiDAR, Object detection, Point cloud},
	isbn = {9781450335621},
	doi = {10.1145/2899361.2899370},
	author = {Mund, Johannes and Zouhar, Alexander and Meyer, Lothar and Fricke, Hartmut and Carsten Rother}
}
