1. A method for automatically recognizing or verifying objects in a digital image, said method comprising: accessing digital image data containing an object of interest therein; using at least one processor for detecting an object of interest in said digital image data of interest in said digital image data; normalizing said object of interest to generate a normalized object representation; extracting a plurality of features from said normalized object representation; and applying each extracted feature to a previously-determined additive probability model to determine the likelihood that the object of interest belongs to an existing class of objects, wherein said additive probability model models the objects using a class center and residual components between the objects and the class center, wherein an uncertainty related to the class center is represented by a model associated with the class center, wherein said object of interest is a face and said step of detecting the object of interest detects facial features in said digital image data.