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Systems for detecting and tracking social marine mammals, including dolphins, can provide data to help explain their social dynamics, predict their behavior, and measure the impact of human interference. Data collected from video surveillance methods can be consistently and systematically sampled for studies of behavior, and frameby-frame analyses can uncover insights impossible to observe from real-time, freely occurring natural behavior. Advances in boat-based, aerial, and underwater recording platforms provide opportunities to document the behavior of marine mammals and create massive datasets. The use of human experts to detect, track, identify individuals, and recognize activity in video demands significant time and financial investment. This paper examines automated methods designed to analyze large video corpora containing marine mammals. While research is converging on best solutions for some automated tasks, particularly detection and classification, many research domains are ripe for exploration.

Automated Video Surveillance for the Study of Marine Mammal Behavior and Cognition