More information on my KTH web pages.
The research at SLU is aimed towards the application of AI methods to recognize, measure and interpret animal motion and behavior in video. The current projects, in collaboration with Elin Hernlund and Pia Haubro Andersen, are mainly targeted towards horse, but my goal during the two-year Guest Professorship is to widen the scope to more species, and also to find new animal AI applications.
Felix Järemo Lawin, Anna Byström, Christoffer Roepstorff, Marie Rhodin, Mattias Almlöf, Mudith Silva, Pia Haubro Andersen, Hedvig Kjellström, and Elin Hernlund. Is Markerless More or Less? Comparing a smartphone computer vision method for equine lameness assessment to multi-camera motion capture. Animals, doi: 10.3390/ani13030390, 2023.
Sofia Broomé, Marcelo Feighelstein, Anna Zamansky, Gabriel Carreira Lencioni, Pia Haubro Andersen, Francisca Pessanha, Marwa Mahmoud, Hedvig Kjellström, and Albert Ali Salah. Going deeper than tracking: A survey of computer-vision based recognition of animal pain and affective state. International Journal of Computer Vision, doi: 10.1007/s11263-022-01716-3 , 2023.
Sofia Broomé, Katrina Ask, Maheen Rashid, Pia Haubro Andersen, and Hedvig Kjellström. Sharing pain: Using pain domain transfer for video recognition of low grade orthopedic pain in horses. PLOS ONE 17(3):e0263854, 2022.
Pia Haubro Andersen, Sofia Broomé, Maheen Rashid, Johan Lundblad, Katrina Ask, Zhenghong Li, Elin Hernlund, Marie Rhodin, and Hedvig Kjellström. Towards machine recognition of facial expressions of pain in horses. Animals, doi: 10.3390/ani11061643, 2021.
Ci Li, Nima Ghorbani, Sofia Broomé, Maheen Rashid, Michael J. Black, Elin Hernlund, Hedvig Kjellström, and Silvia Zuffi. hSMAL: Detailed horse shape and pose reconstruction for motion pattern recognition. In CVPR Workshop on Computer Vision for Animal Behavior Tracking and Modeling, 2021.
Zhenghong Li, Sofia Broomé, Pia Haubro Andersen, and Hedvig Kjellström. Automated detection of equine facial action units, arXiv:2102.08983, 2021.
Sofia Broomé, Karina Bech Gleerup, Pia Haubro Andersen, and Hedvig Kjellström. Dynamics are important for the recognition of equine pain in video. In IEEE Conference on Computer Vision and Pattern Recognition, 2019.