Compared with the ground-based traffic surveillance systems, the airborne platform takes advantage of convenience and low cost. In most of the existing aerial-based systems, the airborne platform is only responsible for data collection and the ground station is in charge of all data processing for vehicle detection. However, such architecture has a low real-time performance unless with the support of specifically constructed wireless networks. This paper proposed an airborne traffic surveillance system, which can detect vehicles in real time with only a general narrowband wireless network support. In our system, the airborne platform not only gathers video information but also carries out data pre-processing, and only the useful data is transferred to the ground via a GPRS/EDGE network. Moreover, more accurate vehicle flow detection with a false-alarm reduction module is performed on the ground station. Experimental results preliminarily show that the system can achieve real-time vehicle flow detection with a high detection rate and a low false-alarm rate.
Angel, A., Hickman, M., Mirchandani, P. and Chandnani, D.2002: Methods of traffic data collection, using aerial video . Proceedings of the IEEE 5th International Conference on Intelligent Transportation Systems, 31-36.
2.
Angel, A., Hickman, M., Mirchandani, P. and Chandnani, D.2002: Application of aerial video for traffic flow monitoring and management. Proceedings of the 7th International Conference on Applications of Advanced Technology in Transportation, 346-53.
3.
Angel, A., Hickman, M., Mirchandani, P. and Chandnani, D.2003: Methods of analyzing traffic imagery collected from aerial platforms. IEEE Transactions on Intelligent Transportation Systems, 4, 99-107.
4.
Chan, C.Y. and Marco, D.2004: Traffic monitoring at signal-controlled intersections and data mining for safety applications. Proceedings of the 7th IEEE International Conference on Intelligent Transportation Systems , 355-60.
5.
Cohen, I. and Medioni, G.1998: Detecting and tracking moving objects in video from an airborne observer. Proceedings of the IEEE Image Understanding Workshop, 217-22.
6.
Coifman, B., Beymer, D., McLauchlan, P. and Malik, J.1999: A real-time computer vision system for vehicle tracking and traffic surveillance. Transportation Research - Part C6, 271-88.
7.
Coifman, B., McCord, M., Mishalani, R.G., Iswalt, M. and Ji, Y.2006: Roadway traffic monitoring from an unmanned aerial vehicle . Proceedings of the IEEE International Conference on Intelligent Transportation Systems, 153, 11-20.
8.
Hirvonen, D., Matei, B., Wildes, R. and Hsu, S.A.H.S.2001: Video to reference image alignment in the presence of sparse features and appearance change. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2, II-366-73.
9.
Kaaniche, K., Champion, B., Pegard, C. and Vasseur, P.2005: A vision algorithm for dynamic detection of moving vehicles with a UAV. Proceedings of the IEEE International Conference on Robotics and Automation, 1878-83.
10.
Klein, L.A., Mills, M.K. and Gibson, D.P.R.2006: Traffic detector handbook: third edition- Volume I. http://www.tfhrc.gov/its/pubs/06108/06108.pdf.
11.
Kumar, R., Sawhney, H., Samarasekera, S., Hsu, S., Tao, H., Guo, Y., Hanna, K., Rope, A., Wildes, R., Hirvonen, D., Hansen, M. and Burt, P.2001: Aerial video surveillance and exploitation. Proceedings of the IEEE89, 1518-39.
12.
Medioni, G., Cohen, I., BreÂmond, F., Hongeng, S. and Nevatia, R.2001: Event detection and analysis from video streams. IEEE Transactions on Pattern Analysis and Machine Intelligence23, 873-89.
13.
Mimbela, L.E.Y. and Klein, L.A.2000: A summary of vehicle detection and surveillance technologies used in intelligent transportation systems. http://www.fhwa.dot.gov/ohim/tvtw/vdstits.pdf.
14.
Nordberg, K., Doherty, P., Forssen, P.E., Wiklund, J. and Andersson, P.2006: A flexible runtime system for image processing in a distributed computational environment for an unmanned aerial vehicle. International Journal of Pattern Recognition and Artificial Intelligence20, 763-80.
15.
Parameswaran, V., Burlina, P. and Chellappa, R.1997: Performance analysis and learning approaches for vehicle detection and counting in aerial images. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing4, 2753-56.
16.
Redding, N.J., Booth, D.M. and Jones, R.2005: Urban video surveillance from airborne and ground-based platforms. Proceedings of the IEEE International Symposium on Imaging for Crime Detection and Prevention, 79-84.
17.
Shastry, A.C. and Schowengerdt, R.A.2005: Airborne video registration and traffic-flow parameter estimation. IEEE Transactions on Intelligent Transportation Systems6, 391-405.
18.
Srinivasan, S., Latchman, H., Shea, J., Wong, T. and McNair, J.2004: Airborne traffic surveillance systems: video surveillance of highway traffic. Proceedings of the ACM 2nd International Workshop on Video Surveillance & Sensor Networks, 131-35.
19.
Wang, G.Z. and Liang, B.1997: Automatic detecting system for traffic flow of bicycles based on pattern recognition and classification. Proceedings of the IEEE International Conference on Systems, Man and Cybernetics5, 4360-63.
20.
Workum, J.A. and Blask, S.G.2001: Adding precision to airborne video with model based registration . Proceedings of the 2nd International Workshop on Digital and Computational Video, 44-51.
21.
Yoneyama, A., Yeh, C.H. and JayKuo, C.C.2005: Robust vehicle and traffic information extraction for highway surveillance. Eurasip Journal on Applied Signal Processing2005, 2305-21.
22.
Yuping, L. and Medioni, G.2007: Map-enhanced UAV image sequence registration and synchronization of multiple image sequences. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 1-7.
