Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota
The complexity and congestion of current transportation systems often produce traffic situations that jeopardize the safety of
the people involved. These situations vary from maintaining a safe distance behind a leading vehicle to safely allowing a
pedestrian to cross a busy street. Environmental sensing plays a critical role in virtually all of these situations. Of the sensors
available, vision sensors provide information that is richer and more complete than other sensors, making them a logical choice
for a multisensor transportation system. In this report we propose robust detection and tracking techniques for intelligent
vehicle-highway applications where computer vision plays a crucial role. In particular, we demonstrate that the Controlled
Active Vision framework  can be utilized to provide a visual tracking modality to a traffic advisory system in order to
increase the overall safety margin in a variety of common traffic situations. We have selected two application examples,
vehicle tracking and pedestrian tracking, to demonstrate that the framework can provide precisely the type of information
required to effectively manage the given traffic situation.
Center for Transportation Studies
ITS Institute Program
Papanikolopoulos, Nikolaos P..
Using CCD Cameras for Obstacle Avoidance and Detection of Pedestrians.
Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota.
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