DogFLW：野外犬类面部关键点数据集
DogFLW: Dog Facial Landmarks in the Wild Dataset
AI总结：
针对动物面部表情自动分析数据不足的问题，本文借鉴猫脸关键点数据集，构建含3,274张图像、46个解剖关键点标注的 DogFLW 犬脸数据集。
摘要：
动物情感计算是一个快速扩展的研究领域，其研究正超越自动化运动追踪，深入探讨疼痛和情绪等动物内部状态。面部表情可用于传达哺乳动物的这些状态信息。然而，与人类相关研究不同，可用于自动分析动物面部表情的数据集严重短缺。受近期推出的 Cat Facial Landmarks in the Wild 数据集启发——该数据集提供了标注48个基于面部解剖结构关键点的猫脸图像——本文构建了一个类似数据集，包含3,274张带标注的犬类图像。我们的数据集采用46个基于面部解剖结构的关键点方案。DogFLW 数据集可向通讯作者提出合理请求后获取。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
