Automated Detection of Pain in Horses through Facial Expression Analysis

Abstract

A method for automated pain-assessment in horses through facial-expression analysis is proposed. The method is based on supervised linear classification of a feature stack of Gabor filters and has the desirable quality of not requiring expert knowledge or specialized equipment to make an assessment. The method is evaluated by applying it to images of horses from two clinical trials where the horses were (ethically) subjected to pain. The resulting accuracy of 78% compares favorably to an alternate method of pain assessment based on facial expression cues that requires expertise to administer.