Evaluating the performance of semiautomated photographic identification programs for leopard seals

Abstract

The photographic identification (photo‐ID) of individual animals can be time‐consuming and erroneous. Recent efforts to collect photographs of leopard seals (Hydrurga leptonyx) from across their range have necessitated the technological streamlining of photo‐ID. We constructed a dataset containing 595 photographs of the head and body of individuals recorded in New Zealand between 2008 and 2022 to test the performance of semiautomated 3 photo‐ID programs: HotSpotter, Interactive Individual Identification System's Pattern+ (I3S), and Wild‐ID. We classified attributes of photographs (e.g., quality) and individuals (i.e., pelage patterns) to assess their effect on performance. We compared performance using Top20 and Top1 Accuracy, defined as the proportion of test photographs where the highest ranked correct identity was in the top 20 and top 1, respectively, matched reference photographs. HotSpotter outperformed I3S and Wild‐ID in both Top20 and Top1 Accuracy of most assessed attributes. Maximizing HotSpotter's performance may be achieved through several methods, including increasing the number and variety of photographs of individuals in the dataset. HotSpotter will likely perform better with photographs without obstructions (e.g., debris from beaches), such as on the pack ice of their primary Antarctic range. We highlight the viability of HotSpotter in assisting the photo‐ID of leopard seals, and more broadly, other species with similar markings.