Equine Utrecht University Scale for Automated Recognition in Facial Assessment of Pain - EQUUS-ARFAP

Abstract

The EQUUS-ARFAP, or the Equine Utrecht University Scale for Automated Recognition in Facial Assessment of Pain, is a project striving to lay the foundations for and prove the feasibility of an application that can automatically assess pain-levels in horses through facial photos. So far only one similar project exists that works on sheep, which is why this project aims to expand upon and broaden this field of automated pain recognition tools for animals and veterinary use. The theory behind the application is based on a combination of the EQUUS-FAP and the HGS pain scoring systems, combining their scoring systems into a single-moment facial-data only pain-scoring scale which is applicable on facial photographs of horses. To create a first version of this application several computer-vision based techniques were used that have been founded on human facial feature recognition. These have been altered to work on the facial features of horses, through the use of medical information available on them. Active shape models, histograms of gradients, colour space conversions, image thinning, support vector machines and cross validation are some of the techniques that were used to realize this application. Results comparable to those of a similar application have been achieved, so it can be safely concluded that this kind of application is feasible and that a basis for future research to continue from has been provided.