activity
20192021
most citedhSMAL: Detailed Horse Shape and Pose Reconstruction for Motion Pattern Recognition

14 citations · 14 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2021

Equine Pain Behavior Classification via Self-Supervised Disentangled Pose Representation

Maheen Rashid, Sofia Broomé, Katrina Ask +4

Timely detection of horse pain is important for equine welfare. Horses express pain through their facial and body behavior, but may hide signs of pain from unfamiliar human observe…

cs.CV202114 cited

hSMAL: Detailed Horse Shape and Pose Reconstruction for Motion Pattern Recognition

Ci Li, Nima Ghorbani, Sofia Broomé +5

In this paper we present our preliminary work on model-based behavioral analysis of horse motion. Our approach is based on the SMAL model, a 3D articulated statistical model of ani…

cs.CV2021

Automated Detection of Equine Facial Action Units

Zhenghong Li, Sofia Broomé, Pia Haubro Andersen +1

The recently developed Equine Facial Action Coding System (EquiFACS) provides a precise and exhaustive, but laborious, manual labelling method of facial action units of the horse.…

cs.CV2020

Interpreting video features: a comparison of 3D convolutional networks and convolutional LSTM networks

Joonatan Mänttäri, Sofia Broomé, John Folkesson +1

A number of techniques for interpretability have been presented for deep learning in computer vision, typically with the goal of understanding what the networks have based their cl…

cs.CV2019

Dynamics are Important for the Recognition of Equine Pain in Video

Sofia Broomé, Karina Bech Gleerup, Pia Haubro Andersen +1

A prerequisite to successfully alleviate pain in animals is to recognize it, which is a great challenge in non-verbal species. Furthermore, prey animals such as horses tend to hide…