  Signal-based Surveillance systems such as Closed Circuits Televisions (CCTV)
have been widely installed in public places. Those systems are normally used to
find the events with security interest, and play a significant role in public
safety. Though such systems are still heavily reliant on human labour to
monitor the captured information, there have been a number of automatic
techniques proposed to analysing the data. This article provides an overview of
automatic surveillance event detection techniques . Despite it's popularity in
research, it is still too challenging a problem to be realised in a real world
deployment. The challenges come from not only the detection techniques such as
signal processing and machine learning, but also the experimental design with
factors such as data collection, evaluation protocols, and ground-truth
annotation. Finally, this article propose that multi-disciplinary research is
the path towards a solution to this problem.
