1. A multi-class classifier combination system comprising: at least one processor; a plurality of multi-class classifiers, each classifier executing on one of the at least one processor, each classifier for classifying a target feature captured in at least one feature stream; and a combination module for combining classifier outputs into a joint prediction, wherein each multi-class classifier prediction is weighted in accordance with a per-class weighting scheme prior to combining, wherein the per-class weighting scheme carried out by the combination module is in accordance with P s ≈ ∑ λ ⁢ w λ [ ∑ ω ~ ⁢ P λ ⁡ ( ω ❘ ω ~ ) ⁢ P λ ⁡ ( ω ~ ❘ x ) ] , where P S is the joint prediction, x is a set of features in a given scene, P λ ({tilde over (ω)}|x) is the prediction of the individual classifier, w λ is a per-classifier weight, and confidence measure, P λ (ω|{tilde over (ω)},x), is approximated by its projection, P λ (ω|{tilde over (ω)}), wherein ω is a true class label and {tilde over (ω)} is an output of an individual multi-class classifier.