Adding precision to airborne video with model based registration

Workum, J.A. Van; Blask, Steven

doi:10.1109/dcv.2001.929941

Cited by 3 publications

(1 citation statement)

References 2 publications

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“…The second frame is translated or rotated to compensate the movement of the airborne platform itself, and then the two frames can be considered to be taken from a stationary platform. For frame registration, many onground processing methods were proposed for airborne videos (Angel et al, 2002b;Hirvonen et al, 2001;Shastry and Schowengerdt, 2005;Workum and Blask, 2001;Yuping and Medioni, 2007). These methods have high accuracy; however, they might not be suitable for on-board processing because of high computational complexity.…”

Section: Frame Registrationmentioning

confidence: 99%

Vehicle flow detection in real-time airborne traffic surveillance system

Luo

Huang

et al. 2011

Transactions of the Institute of Measurement and Control

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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.

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Section: Frame Registrationmentioning

confidence: 99%