26. A method for object fingerprinting as set forth in claim 25 , further comprising acts of: segmenting a potential object candidate from a sequence of video frames taken from a scene using a flow-based object segmentation module, and communicating the segmented potential object candidate to the oriented localized filter module for iconic feature extraction; and predicting a general class of the potential object candidate using a incremental learning module.
27. A method for object fingerprinting as set forth in claim 26 , further comprising acts of: extracting a relevant feature set from the potential object candidate using a fixed-basis function decomposition module using Haar wavelets; classifying the potential object candidate using a static classifier, thereby generating a classification category selected from a group consisting of a positive identification, a negative identification, a false positive identification, and a false negative identification, and where upon classification, the static classifier communicates the classification to the incremental learning module.