The Northumberland Dolphin Dataset: A Multimedia Individual Cetacean Dataset for Fine-Grained Categorisation
This dataset addresses the bottleneck of manual categorization in cetacean research, though it is incremental as it provides new data rather than a novel method.
The paper introduces the Northumberland Dolphin Dataset (NDD), a multimedia dataset of images and spectrograms from white-beaked dolphins, aimed at automating fine-grained categorization to reduce the human-hours needed for cetacean research.
Methods for cetacean research include photo-identification (photo-id) and passive acoustic monitoring (PAM) which generate thousands of images per expedition that are currently hand categorised by researchers into the individual dolphins sighted. With the vast amount of data obtained it is crucially important to develop a system that is able to categorise this quickly. The Northumberland Dolphin Dataset (NDD) is an on-going novel dataset project made up of above and below water images of, and spectrograms of whistles from, white-beaked dolphins. These are produced by photo-id and PAM data collection methods applied off the coast of Northumberland, UK. This dataset will aid in building cetacean identification models, reducing the number of human-hours required to categorise images. Example use cases and areas identified for speed up are examined.