Modern surveillance systems collect a massive amount of data.
In contrast to conventional systems that store raw sensor material, modern
systems take advantage of smart sensors and improvements in image processing.
They extract relevant information about the observed objects of interest,
which is then stored and processed during the surveillance process. Such
high-level information is, e.g., used for situation analysis and can be processed
in different surveillance tasks. Modern systems have become powerful,
can potentially collect all kind of user information and make it available
to any surveillance task. Hence, direct access to the collected high-level data
must be prevented. Multiple approaches for anonymization exist, but they
do not consider the special requirements of surveillance tasks. This work
examines and evaluates existing metrics for anonymization and approaches
for anonymization. Even though all kind of data can be collected, position
data is still the one with the highest demand. Hence, this work focuses its
anonymization and proposes an algorithm that fulfills the requirements for
anonymization in surveillance.