Airborne monitoring of vehicle activity in urban areas

We describe possibilities to extract vehicles from data of different airborne sensor systems. We focus on three frequency domains, namely (i) visual, (ii) thermal IR and (iii) radar. Corresponding to the data different processing methods are demanded.(i)Vehicle detection in aerial images relies upon local and global features. For modelling a vehicle on local level, a 3D-wireframe representation is used describing prominent geometric and radiometric features of cars including their shadow region. A vehicle is extracted by a ”top-down” matching of the model to the image. On global level, vehicle queues are modelled by ribbons that exhibit typical symmetries and spacing of vehicles over a larger distance. Fusing local and global extractions makes the result more complete. (ii) Particularly at night video sequences from an infrared camera yields suitable data to assess the activity of vehicles. At the resolution of approximately one meter vehicles appear as elongated spots. However, in urban areas many additional other objects have the same property. Vehicles may be discriminated from these objects either by their movement or by their temperature and their appearance in groups. Additional knowledge from a vector maps is helpful. The grouping of vehicles into rows along the margins of the roads is performed by using of map knowledge as context. (iii) The increasing resolution of SAR data opens the possibility to detect vehicles even under bad weather conditions. Along-track interferometry allows to estimate vehicle movement. However, in urban areas SAR specific illumination phenomena like foreshortening, layover, shadow, and multipath-propagation burden the interpretation. Particularly the visibility of the vehicles in inner city areas is in question. A high resolution LIDAR DEM is incorporated to determine the visibility of the roads by a SAR measurement from a given sensor trajectory and sensor orientation. Shadow and layover areas are detected by incoherent sampling of the DEM. In order to determine the optimal flight path a large number of simulations are carried out with varying viewing and aspect angles.
Stilla U, Michaelsen E, Soergel U, Hinz S, Ender HJ (2004) Airborne monitoring of vehicle activity in urban areas. In: Altan MO (ed) International Archives of Photogrammetry and Remote Sensing. Vol 35, Part B3, 973-979
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