Categorization of Underwater Habitats Using Dynamic Video Textures (2013).
Jun Hu, Han Zhang, Anastasia Miliou, Thodoris Tsimpidis, Hazel Thornton, Vladimir Pavlovic
In this paper, we deal with the problem of categorizing different underwater habitat types. Previous works on solving this categorization problem are mostly based on the analysis of underwater images. In our work, we design a system capable of categorizing underwater habitats based on underwater video content analysis since the temporally correlated information may make contribution to the categorization task. However, the task is very challenging since the underwater scene in the video is continuously varying because of the changing scene and surface conditions, lighting, and the viewpoint.