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In this paper we present our preliminary work on model-based behavioralanalysis of horse motion. Our approach is based on the SMAL model, a 3Darticulated statistical model of animal shape. We define a novel SMAL model forhorses 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 horsefrom 3D mocap data and images. We apply the hSMAL model to the problem oflameness detection from video, where we fit the model to images to recover 3Dpose and train an ST-GCN network on pose data. A comparison with the samenetwork trained on mocap points illustrates the benefit of our approach.

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