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Automated Detection of Equine Facial Action Units

2021-02-17 19:22:39
Zhenghong Li, Sofia Broomé, Pia Haubro Andersen, Hedvig Kjellström
arXiv_CV
               
Abstract

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. To automate parts of this process, we propose a Deep Learning-based method to detect EquiFACS units automatically from images. We use a cascade framework; we firstly train several object detectors to detect the predefined Region-of-Interest (ROI), and secondly apply binary classifiers for each action unit in related regions. We experiment with both regular CNNs and a more tailored model transferred from human facial action unit recognition. Promising initial results are presented for nine action units in the eye and lower face regions.

Abstract (translated)

URL

https://arxiv.org/abs/2102.08983

PDF

https://arxiv.org/pdf/2102.08983.pdf

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