2021/05/28 by Ilia Chelak, Chelak, Ilia, Ekaterina Nepovinnykh +7
Agricultural and Biological Sciences · Biochemistry, Genetics and Molecular Biology · Environmental Science · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Food Supply Chain Traceability #Identification and Quantification in Food #Marine animal studies overview
paper · pdf · doi:10.48550/arxiv.2105.13979
openalex publication_date 2021/05/28 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
In this paper, pelage pattern matching is considered to solve the individual re-identification of the Saimaa ringed seals. Animal re-identification together with the access to large amount of image material through camera traps and crowd-sourcing provide novel possibilities for animal monitoring and conservation. We propose a novel feature pooling approach that allow aggregating the local pattern features to get a fixed size embedding vector that incorporate global features by taking into account the spatial distribution of features. This is obtained by eigen decomposition of covariances computed for probability mass functions representing feature maps. Embedding vectors can then be used to find the best match in the database of known individuals allowing animal re-identification. The results show that the proposed pooling method outperforms the existing methods on the challenging Saimaa ringed seal image data.