APS is a model that utilises a Gaussian Markov Random Field (GMRF) for learning an appearance model with pairwise distributions based on a graph. It also has a parametric statitical shape model (either using PCA or GMRF), as well as a spring-like deformation prior term. The optimisation is performed using a weighted Gauss-Newton algorithm with fixed Jacobian and Hessian.
GenerativeAPS
GaussNewtonAPSFitter
Inverse Forward
APSResult APSAlgorithmResult