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Forskningsartikel2023Vetenskapligt granskadÖppen tillgång

Going Deeper than Tracking: A Survey of Computer-Vision Based Recognition of Animal Pain and Emotions

Broome, Sofia; Feighelstein, Marcelo; Zamansky, Anna; Lencioni, Gabriel Carreira; Andersen, Pia Haubro; Pessanha, Francisca; Mahmoud, Marwa; Kjellstrom, Hedvig; Salah, Albert Ali

Sammanfattning

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 pain and emotional states 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.

Nyckelord

Affective computing; Non-human behavior analysis; Pain estimation; Pain recognition; Emotion recognition; Computer vision for animals

Publicerad i

International Journal of Computer Vision
2023, Volym: 131, sidor: 572-590
Utgivare: SPRINGER

    UKÄ forskningsämne

    Datorseende och robotik (autonoma system)
    Husdjursvetenskap

    Publikationens identifierare

    DOI: https://doi.org/10.1007/s11263-022-01716-3

    Permanent länk till denna sida (URI)

    https://res.slu.se/id/publ/120393