2023/08/11 by Veikka Immonen, Ekaterina Nepovinnykh, Immonen, Veikka +7
Biochemistry, Genetics and Molecular Biology · Environmental Science · #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Ichthyology and Marine Biology #Identification and Quantification in Food #Marine animal studies overview
paper · pdf · doi:10.48550/arxiv.2308.06335
openalex publication_date 2023/08/11 · openalex created_date 2023/08/16 · openalex updated_date 2026/07/28
Image-based re-identification of animal individuals allows gathering of information such as migration patterns of the animals over time. This, together with large image volumes collected using camera traps and crowdsourcing, opens novel possibilities to study animal populations. For many species, the re-identification can be done by analyzing the permanent fur, feather, or skin patterns that are unique to each individual. In this paper, we address the re-identification by combining two types of pattern similarity metrics: 1) pattern appearance similarity obtained by pattern feature aggregation and 2) geometric pattern similarity obtained by analyzing the geometric consistency of pattern similarities. The proposed combination allows to efficiently utilize both the local and global pattern features, providing a general re-identification approach that can be applied to a wide variety of different pattern types. In the experimental part of the work, we demonstrate that the method achieves promising re-identification accuracies for Saimaa ringed seals and whale sharks.