Information Systems Department, University of Haifa, Haifa, Israel.
Computer Science Department, University of Haifa, Haifa, Israel.
PLoS One. 2024 Jul 15;19(7):e0302893. doi: 10.1371/journal.pone.0302893. eCollection 2024.
Animal affective computing is an emerging new field, which has so far mainly focused on pain, while other emotional states remain uncharted territories, especially in horses. This study is the first to develop AI models to automatically recognize horse emotional states from facial expressions using data collected in a controlled experiment. We explore two types of pipelines: a deep learning one which takes as input video footage, and a machine learning one which takes as input EquiFACS annotations. The former outperforms the latter, with 76% accuracy in separating between four emotional states: baseline, positive anticipation, disappointment and frustration. Anticipation and frustration were difficult to separate, with only 61% accuracy.
动物情感计算是一个新兴的领域，迄今为止主要集中在疼痛方面，而其他情绪状态仍是未知领域，尤其是在马中。本研究首次开发了人工智能模型，使用在受控实验中收集的数据，自动从面部表情识别马的情绪状态。我们探索了两种类型的管道：一种是深度学习，其输入是视频片段；另一种是机器学习，其输入是 EquiFACS 注释。前者优于后者，在区分四种情绪状态（基线、积极期待、失望和挫折）方面的准确率为 76%。期待和挫折难以区分，准确率仅为 61%。
