Going deeper than tracking: a survey of computer-vision based recognition of animal pain and emotions

Broomé, S., Feighelstein, M., Zamansky, A., Carreira Lencioni, G., Haubro Andersen, P., Pessanha, F., Mahmoud, M. , Kjellström, H. and Salah, A. A. (2023) Going deeper than tracking: a survey of computer-vision based recognition of animal pain and emotions. International Journal of Computer Vision, 131(2), pp. 572-590. (doi: 10.1007/s11263-022-01716-3)

Abstract

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.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Mahmoud, Dr Marwa
• Authors: Broomé, S., Feighelstein, M., Zamansky, A., Carreira Lencioni, G., Haubro Andersen, P., Pessanha, F., Mahmoud, M., Kjellström, H., and Salah, A. A.
• College/School: College of Science and Engineering > School of Computing Science
• Journal Name: International Journal of Computer Vision
• Publisher: Springer
• ISSN: 0920-5691
• ISSN (Online): 1573-1405
• Published Online: 25 November 2022
• Copyright Holders: Copyright © 2022 The Authors
• First Published: First published in International Journal of Computer Vision 131(2): 572-590
• Publisher Policy: Reproduced under a Creative Commons licence