39. The computer system of claim 37 , which, upon being programmed, is further configured to provide lighting adjustments to the transform coefficients prior to applying the plurality of view-based classifiers.
37. A computer system, which, upon being programmed, is configured to perform the following: compute, using one or more data processors, a transform of a digitized version of a 2D (two-dimensional) image containing a 2D representation of an object, wherein said transform generates a plurality of transform coefficients; apply, using the one or more data processors, a plurality of view-based classifiers to the plurality of transform coefficients, wherein each view-based classifier is configured to detect a specific orientation of said object in said 2D image based on visual information received from corresponding transform coefficients, wherein at least one of said plurality of view-based classifiers includes a plurality of cascaded sub-classifiers, and wherein at least one of said plurality of sub-classifiers is based on a ratio of a plurality of graphical probability models; wherein a classifier is determined by: applying a view-based classifier to said 2D image, wherein said classifier includes a plurality of sub-classifiers; computing a sum of log-likelihood ratios for each of said plurality of sub-classifiers, wherein said log-likelihood ratio is a ratio of two graphical probability models; wherein a graphical probability model comprises a probability distribution over a set of variables where statistical independence and conditional statistical independence exist among various combinations of the variables, wherein the graphical probability model is a probability distribution representation derived from statistical dependencies among image input variables; and detect orientation and location of each instance of said object in said 2D image from a combination of results of the application of said plurality of view-based classifiers.