发表机构
Fraunhofer Institute for Computer Graphics Research IGD; Technische Universität Darmstadt（弗劳恩霍夫计算机图形研究所IGD; 达姆施塔特工业大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对奶牛面部识别，构建了含6838张图像的公开基准数据集，定义了评估协议，给出六个基准模型的评估结果，为奶牛面部识别研究提供数据支持与评估标准，推动该领域可比研究。
AI 中文摘要
随着精准畜牧养殖的发展和计算机视觉的进步，视觉动物生物识别受到关注。利用已被证明对人类有效的生物识别技术来识别牲畜，可提高动物福利和生产效率。然而，存在复杂场景、外观相似、遮挡、非合作行为等挑战，且公开可用的标注数据集有限。本文贡献了一个新颖的、公开可用的奶牛面部基准数据集，该数据集是在奶牛场真实自动场景下收集的，包含161头不同奶牛的6838张图像。除了公共数据集，还定义了两个验证和四个识别评估协议，以促进奶牛识别研究领域的可比研究。此外，还给出了六个基准模型在该数据集上的评估结果。
英文摘要
With the development of precision livestock farming and the advances in computer vision, visual animal biometrics has gained attention. Using biometric technologies that have been proven effective for humans to identify livestock can increase animal welfare as well as production efficiency. However, challenges such as complex scenarios, similar appearances, occlusions, and non-cooperative behavior, as well as the limited amount of publicly available labeled datasets, remain. In this work, we contribute a novel, publicly available cow face benchmark dataset that has been collected in a realistic automatic scenario with 6,838 images of 161 different cows at a dairy farm. In addition to the public dataset, we define two verification and four identification evaluation protocols to foster comparable research in the cow recognition research field. Further, we provide evaluation results on our dataset of six benchmark models, which include models trained on limited data, cross-species fine-tuned models, and zero-shot foundation model approaches.
CommentsAccepted at ICPR 2026 Workshops
