Abstract
This paper discusses a trajectory based recognition algorithm to expand the common approaches for atypical event detection in multi-object traffic scenes and to obtain area-based types of information (e.g. maps of speed patterns, trajectory curvatures or erratic movements). Different views of the same area by more than one camera sensor are necessary, because of the typical limitations of single camera systems, resulting from occlusions by other cars, trees and traffic signs. Furthermore, distributed cooperative multi-camera system (MCS) enables a significant enlargement of the observation area. The fusion of object data from different cameras is done by a multi-target tracking approach. This approach opens up opportunities to identify and specify traffic objects, their location, speed and other characteristic object information. New and consolidated information of traffic participants is derived from the system.
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Reulke, R., Meysel, F., Bauer, S. (2008). Situation Analysis and Atypical Event Detection with Multiple Cameras and Multi-Object Tracking. In: Sommer, G., Klette, R. (eds) Robot Vision. RobVis 2008. Lecture Notes in Computer Science, vol 4931. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78157-8_18
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DOI: https://doi.org/10.1007/978-3-540-78157-8_18
Publisher Name: Springer, Berlin, Heidelberg
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