Figure 2. (left) A schematic overview of a camera network and its relation to the geographic network. The inset shows the possible camera to camera transitions. (right) Example of how tracklets from individual cameras might be associated into global tracks through the network of cameras; using the spatio-temporal as well as object appearance.


Consistent tracking

Earlier we briefly discussed the needed for tracking functionality in each individual camera’s field of view. Usually, a normal installation will consist of multiple cameras. Some of these cameras might have overlapping field of views while other pairs might be setup long from each other and have completely different fields of views. For several reasons, a consistent tracking in such a network is a much more challenging problem than tracking in a single field of view:
• The cameras can be widely separated and the object can be out of sight for prolonged times

• The lighting conditions can also be very different making any appearance based object matching a great challenge.

• The cameras themselves can be of different models and their relative setup can vary greatly.
This is a very difficult problem to solve in its entire generality. For example, a brute force attempt would require computations that increase exponentially as the number of cameras and objects increases. However, methods for consistent tracking in networks are evolving to a state where they actually are useful and yield an added value to the end-user. The more successful methods take into consideration how the physical network of entrances/exits, open spaces and hall ways are related to the network of cameras. In this way we only need to associate objects between those fields of view that actually are connected, see Figure 2.
While a consistent tracking in non-overlapping fields of view is still a work in progress, the tracking in overlapping fields of view is nowadays available in commercial systems.

A working network tracking facility can substantially improve the operator’s ability to fulfil the safety and security objectives. First of all, a substantially improved overview of the surveyed area is possible since objects can be traced consistently through the various overlapping and non-overlapping FOVs. Secondly, it becomes possible to assess the earlier whereabouts of the object as well as its future possible routes. Finally, this kind of functionality can be very useful in off-line analysis as well. Since it becomes possible to annotate the recorded video stream with object data, we can efficiently search in the much more condensed meta-data instead of the more cumbersome search in the raw video data.                    

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