11. The method of claim 10 wherein the classifications are combined based on the following equation: H ⁡ ( x i ) = sign ⁡ ( ∑ t = 1 T ⁢ α t ⁢ h t ⁡ ( x i ) ) where H(x i ) is the combined classification for the i-th scene, x i is the feature vector for the i-th scene, T is the number of sub-classifiers, h t is the adjusted t-th sub-classifier, and α is represented by the following equation: α t = 1 2 ⁢ ln ⁡ ( 1 - ɛ t ɛ t ) where ε t represents error of the t-th sub-classifier.
10. The method of claim 9 wherein the generated classifier applies each sub-classifier to feature vectors of the scenes to generate a classification for each scene for each sub-classifier and combines the classifications for a scene based on the weight of the sub-classifier that generated the classification.