12. A method comprising: via a computer processor: performing a semi-supervised least-squares-based alignment of an image ensemble using an inverse warping technique; determining estimated warping parameters of unlabeled images in the image ensemble based on known warping parameters of labeled images of the image ensemble using results of the semi-supervised least-squares-based alignment; reducing outliers of the estimated warping parameters by partitioning a mean shape space of the semi-supervised least-squares-based alignment, wherein partitioning the means shape space includes iteratively partitioning an initially identified patch corresponding to an image of the image ensemble into child patches; and refining landmark estimations based on resultant patch appearance.
15. The method of claim 12 , comprising generating output data including a set of images.