Exploiting 3D information for an automated semantic analysis of underwater images

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Automated image analysis is a common methodology, but has seen little application for underwater imagery. Pattern recognition and machine learning methods are challenged by the peculiar environment. Imaging under water is prone to attenuation, turbidity and varying illumination. Anyhow, several studies have shown success in exploiting 2D information for a semantic interpretation of underwater images. There exist, however, cases where 2D information alone is not sufficient to extract knowledge from the images. In those cases 3D, information could help.Here, an existing 3D data set shall be analysed. It will be complimented by 3D imagery acquired under controlled conditions. Additional morphological information shall be incorporated into automated 2D pattern recognition methods. Joint research with marine biologists will be conducted. Semantic data, automatically extracted from the imagery, will be used for a better spatial understanding of the imaged habitats.