Automatic acquisition and analysis of traffic-related data has alreadya long tradition in the remote sensing community. Similarly airborne laser scanning (ALS) has emerged as an efficient means toacquire the detailed 3D large-scale DSMs. The aim of this work is to initialize research work on using ALS to extract the traffic-flowinformation focusing on urban areas. The laser data acquisition configuration has firstly to be analyzed in order to obtain the optimalperformance with respect to the reconstruction of trafficrelatedobjects. Mutual relationships between various ALS parameters andvehicle modeling in the laser points are to be elaborated. Like other common tasks in object recognition, vehicle models fordetection and motion indication from the laser data are presented; moreover, an ALS simulator is implemented to clarify and validatemotion artifact in laser data. Finally, a concept for recognizingvehicles are proposed based on a vehicle and context model, whichestablishes a direct working flow simulating the human inferenceroutine.     «

Automatic acquisition and analysis of traffic-related data has alreadya long tradition in the remote sensing community. Similarly airborne laser scanning (ALS) has emerged as an efficient means toacquire the detailed 3D large-scale DSMs. The aim of this work is to initialize research work on using ALS to extract the traffic-flowinformation focusing on urban areas. The laser data acquisition configuration has firstly to be analyzed in order to obtain the optimalperformance with respect to the rec...     »