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Advances in animal motion tracking and pose recognition have been a gamechanger in the study of animal behavior. Recently, an increasing number ofworks go 'deeper' than tracking, and address automated recognition of animals'internal states such as emotions and pain with the aim of improving animalwelfare, making this a timely moment for a systematization of the field. Thispaper provides a comprehensive survey of computer vision-based research onrecognition of affective states and pain in animals, addressing both facial andbodily behavior analysis. We summarize the efforts that have been presented sofar within this topic -- classifying them across different dimensions,highlight challenges and research gaps, and provide best practicerecommendations for advancing the field, and some future directions forresearch.

Going Deeper than Tracking: a Survey of Computer-Vision Based Recognition of Animal Pain and Affective States