论文标题
比跟踪更深入：对基于计算机的识别动物疼痛和情感状态的调查
Going Deeper than Tracking: a Survey of Computer-Vision Based Recognition of Animal Pain and Affective States
论文作者
论文摘要
动物运动跟踪和姿势识别的进步一直是研究动物行为的游戏规则改变者。最近，越来越多的作品比跟踪更“深”，并解决了对动物内部状态（例如情绪和痛苦）的自动认识，目的是改善动物福利，这使得这是对该领域进行系统化的及时时刻。本文对基于计算机的识别情感状态和动物疼痛的研究进行了全面的调查，以解决面部行为和身体行为分析。我们总结了迄今为止在这个主题中所付出的努力 - 对它们进行分类，强调挑战和研究差距，并为前进的领域提供最佳实践建议，以及一些未来的研究方向。
Advances in animal motion tracking and pose recognition have been a game changer in the study of animal behavior. Recently, an increasing number of works go 'deeper' than tracking, and address automated recognition of animals' internal states such as emotions and pain with the aim of improving animal welfare, making this a timely moment for a systematization of the field. This paper provides a comprehensive survey of computer vision-based research on recognition of affective states and pain in animals, addressing both facial and bodily behavior analysis. We summarize the efforts that have been presented so far within this topic -- classifying them across different dimensions, highlight challenges and research gaps, and provide best practice recommendations for advancing the field, and some future directions for research.
