Dataset on underwater change detection

The detection of moving objects in a scene is a well researched but depending on the concrete research still often a challenging computer vision task. Usually it is the first step in a whole pipeline and all following algorithms (tracking, classification etc.) are dependent on the accuracy of the detection. Hence, a good pixel-precise segmentation of the objects of interest is mandatory for many applications. However, the underwater environment has mostly been neglected so far and there exists no common dataset to evaluate different algorithms under the harsh underwater conditions and therefore a comprehensive evaluation is impossible. In this paper, we present an underwater change detection dataset consisting of five videos and hundreds of handsegmented ground truth images as well as a survey of different underwater image enhancement techniques and their impact on segmentation algorithms.