1. A system for localizing parts of an object in an input image, the system comprising: at least one computing device configured to: train a plurality of local detectors using at least a portion of a plurality of image exemplars as training images, wherein each image exemplar is labeled with fiducial points corresponding to parts within the image, and wherein each local detector generates a detector score when applied at one location of a plurality of locations of fiducial points in the training images corresponding to a likelihood that a desired part is located at the location within the training image; generate a non-parametric model of the plurality of locations of the fiducial points in each of at least a portion of the plurality of image exemplars; receive data corresponding to the input image; apply the trained local detectors to the input image to generate detector scores for the input image; derive a Bayesian objective function for the input image from the non-parametric model and detector scores; and generate an output comprising locations of the fiducial points within the object in the image.