论文标题
鸟类的眼光：测量鸡的行为和姿势作为其幸福的度量
Birds' Eye View: Measuring Behavior and Posture of Chickens as a Metric for Their Well-Being
论文作者
论文摘要
鸡肉福祉对于确保粮食安全和更好的营养对于不断增长的全球人口很重要。在这项研究中，我们将行为和姿势表示为测量鸡肉健康的指标。为了检测笔中的鸡姿势和行为，我们采用了两种算法：蒙版r-CNN，例如分割和yolov4与resnet50结合使用进行分类。我们的结果表明，使用蒙版R-CNN的姿势和行为检测的加权F1得分为88.46％，行为检测的平均精度为91％，使用Yolov4的姿势检测平均准确度为86.5％。这些实验是在不受控制的场景下进行姿势和行为测量的。这些指标为获得个人和群体行为和姿势的体面迹象奠定了坚实的基础。这样的结果将有助于改善鸡的整体福祉。本研究中使用的数据集是在内部收集的，并将在出版物后公开，因为它将成为未来研究的非常有用的资源。据我们所知，在此工作中，没有其他研究工作涉及多种行为和姿势。
Chicken well-being is important for ensuring food security and better nutrition for a growing global human population. In this research, we represent behavior and posture as a metric to measure chicken well-being. With the objective of detecting chicken posture and behavior in a pen, we employ two algorithms: Mask R-CNN for instance segmentation and YOLOv4 in combination with ResNet50 for classification. Our results indicate a weighted F1 score of 88.46% for posture and behavior detection using Mask R-CNN and an average of 91% accuracy in behavior detection and 86.5% average accuracy in posture detection using YOLOv4. These experiments are conducted under uncontrolled scenarios for both posture and behavior measurements. These metrics establish a strong foundation to obtain a decent indication of individual and group behaviors and postures. Such outcomes would help improve the overall well-being of the chickens. The dataset used in this research is collected in-house and will be made public after the publication as it would serve as a very useful resource for future research. To the best of our knowledge no other research work has been conducted in this specific setup used for this work involving multiple behaviors and postures simultaneously.
