mlsanityData to 7 Oct 2026

Video-based estimation of pain indicators in dogs

arXiv 2209.13296 ↗First posted 27 Sep 2022cs.CVcited by 0

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Abstract (arXiv)

Dog owners are typically capable of recognizing behavioral cues that reveal subjective states of their dogs, such as pain. But automatic recognition of the pain state is very challenging. This paper proposes a novel video-based, two-stream deep neural network approach for this problem. We extract and preprocess body keypoints, and compute features from both keypoints and the RGB representation over the video. We propose an approach to deal with self-occlusions and missing keypoints. We also present a unique video-based dog behavior dataset, collected by veterinary professionals, and annotated for presence of pain, and report good classification results with the proposed approach. This study is one of the first works on machine learning based estimation of dog pain state.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 32 of its 65 references that are in the map. First posted on arXiv 27 Sep 2022.

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32 of 65 references.

References · 32

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20 more
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