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arXiv Computer Vision By David Brunner, Maciej Oczak, Marie Bordes, Jean-Loup Rault, Stephan M. Winkler, Viktoria Dorfer

BMCTrack-d: Pig re-identification and tracking via back marks in challenging camera settings

Read the original on arXiv Computer Vision →

BMCTrack-d is a novel tracking-by-detection method that uses unique back marks on pigs to achieve robust re-identification and tracking in challenging side-view camera settings. The approach employs a neural network-based back mark classifier followed by temporal consistency checks and deduplication to improve identity reliability over time. On a demanding test set, BMCTrack-d outperforms strong baselines, achieving higher-order tracking accuracy gains of 9.11% and 1.03%.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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