Figure 1. Computer Expression Recognition Toolbox video processing pipeline.

Video segments are analyzed on a frame-by-frame basis. Within the frame image, faces are located with the use of standard facial landmarks. After the face is found, Gabor features are extracted and used in a high-dimensional support vector machine (SVM) large-margin linear classifier, and the distance of the patient's metrics from the hyperplane determines the normalized eye closure magnitude, in arbitrary units (modified from Littlewort et al.,¹⁰ figure 2, with permission).