Abstract:
Many large cities have installed surveillance cameras to monitor 
and record human activities for security purposes. An important
surveillance application is to track the motion of an object of
interest, e.g., a car or a human, using one or more cameras, and 
plot the motion path in a city map. To achieve this goal, it is 
necessary to localize the cameras in the city map and to determine
the correspondence mappings between the positions in the city map
and the camera views. Since the view of the city map is roughly
orthogonal to the camera views, there are very few common features 
between the two views for a computer vision algorithm to correctly 
identify corresponding points automatically.This talk presents a 
method for camera localization and position mapping that requires 
minimum user inputs. Given approximate corresponding points 
between the city map and a camera view identified by a user, the 
method computes the orientation and position of the camera in the 
city map, and determines the mapping between the positions in the 
city map and the camera view. Both quantitative tests and practical
application test have been performed.