  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 animal shape. We define a novel SMAL model for
horses based on a new template, skeleton and shape space learned from $37$
horse toys. We test the accuracy of our hSMAL model in reconstructing a horse
from 3D mocap data and images. We apply the hSMAL model to the problem of
lameness detection from video, where we fit the model to images to recover 3D
pose and train an ST-GCN network on pose data. A comparison with the same
network trained on mocap points illustrates the benefit of our approach.
