Seal Re Identification

Seal re-identification focuses on automatically identifying individual seals from images, primarily using their unique pelage patterns. Current research employs computer vision techniques, such as convolutional neural networks (CNNs) and U-net architectures, often incorporating feature aggregation methods like Fisher Vectors to improve accuracy in challenging conditions (e.g., varying poses, low contrast). This technology facilitates efficient monitoring of endangered seal populations, enabling more accurate population size estimations and studies of animal behavior and migration patterns, contributing significantly to conservation efforts.