Affective computing for animals is a rapidly expanding research area that is
going deeper than automated movement tracking to address animal internal
states, like pain and emotions. Facial expressions can serve to communicate
information about these states in mammals. However, unlike human-related
studies, there is a significant shortage of datasets that would enable the
automated analysis of animal facial expressions. Inspired by the recently
introduced Cat Facial Landmarks in the Wild dataset, presenting cat faces
annotated with 48 facial anatomy-based landmarks, in this paper, we develop an
analogous dataset containing 3,274 annotated images of dogs. Our dataset is
based on a scheme of 46 facial anatomy-based landmarks. The DogFLW dataset is
available from the corresponding author upon a reasonable request.

动物情感计算是一个快速发展的研究领域，目前关注于动物内部状态的自动追踪，如疼痛和情绪，动物的面部表情可以用来传达这些状态信息，本文基于狗的面部解剖标志物的方案，开发了一个包含 3274 张狗的图像的数据集，名为 DogFLW 数据集。