  This essay reviews human observer-based methods employed in shark spotting in
Muizenberg Beach. It investigates Machine Learning methods for automated shark
detection with the aim of enhancing human observation. A questionnaire and
interview were used to collect information about shark spotting, the motivation
of the actual Shark Spotter program and its limitations. We have defined a list
of desirable properties for our model and chosen the adequate mathematical
techniques. The preliminary results of the research show that we can expect to
extract useful information from shark images despite the geometric
transformations that sharks perform, its features do not change. To conclude,
we have partially implemented our model; the remaining implementation requires
dataset.
