Diving with Penguins: Detecting Penguins and their Prey in Animal-borne Underwater Videos via Deep Learning

TL;DR

This paper presents a deep learning system for detecting penguins, fish, and predation behaviors in underwater videos, providing valuable tools and datasets for marine biology conservation efforts.

Contribution

It introduces a robust deep learning detector for penguins and fish, along with the first attempt at automated predation behavior recognition in underwater penguin videos.

Findings

Penguin detector achieves mAP50@98.0%.

Fish detector achieves mAP50@73.3%.

First results on behavior recognition in marine predator videos.

Abstract

African penguins (Spheniscus demersus) are an endangered species. Little is known regarding their underwater hunting strategies and associated predation success rates, yet this is essential for guiding conservation. Modern bio-logging technology has the potential to provide valuable insights, but manually analysing large amounts of data from animal-borne video recorders (AVRs) is time-consuming. In this paper, we publish an animal-borne underwater video dataset of penguins and introduce a ready-to-deploy deep learning system capable of robustly detecting penguins (mAP50@98.0%) and also instances of fish (mAP50@73.3%). We note that the detectors benefit explicitly from air-bubble learning to improve accuracy. Extending this detector towards a dual-stream behaviour recognition network, we also provide the first results for identifying predation behaviour in penguin underwater videos. Whilst results are promising, further work is required for useful applicability of predation behaviour detection in field scenarios. In summary, we provide a highly reliable underwater penguin detector, a fish detector, and a valuable first attempt towards an automated visual detection of complex behaviours in a marine predator. We publish the networks, the DivingWithPenguins video dataset, annotations, splits, and weights for full reproducibility and immediate usability by practitioners.