32. The system of claim 31 , wherein said means for obtaining includes: means for computing a wavelet transform of said 2D image, wherein said wavelet transform generates a plurality of transform coefficients, and wherein each transform coefficient represents a portion of said visual information from said 2D image that is localized in space, frequency, and orientation.
31. A system, comprising: means for receiving a digitized version of a two-dimensional (2D) image containing a 2D representation of a three-dimensional (3D) object; means for obtaining visual information from said digitized version of said 2D image; and means for classifying said 2D image based on a ratio of at least two graphical probability models using said visual information; wherein said classifying includes: 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.