Sammendrag
Aquaculture industry is one of the most sustainable and environmental friendly
way of satisfying the world’s increasing food demand. However, fish escape still
remains a critical challenge that is not only a financial loss but badly effects the
biodiversity as well. These escapes mostly happens through a hole caused by a
natural event or an accident hence it is essential to have a mechanism to detect
it. SLAM(simultaneous localization and mapping) is the current state of the art
method to resolve issues like this. The aim of this thesis is to focus on the Place re-
cognition and loop closure part of the SLAM. BOW technique along with different
feature extraction methods will be evaluated and compared in different realistic
scenarios. Moreover, the performance of these techniques on non net cage marine
data will be also discussed to establish a strong argument.