1. A system for meta-classification of surveillance video comprising: a video acquisition mechanism configured to acquire surveillance video; a training phase mechanism; and an operational phase mechanism; wherein: the training phase mechanism comprises: a detection and tracking module configured to add bounding boxes to interesting objects in a training surveillance video acquired by the video acquisition mechanism; a workstation with a screen configured to allow a human operator to draw bounding boxes on interesting objects in the training surveillance video; a classifier section connected to the detection and tracking module, the classifier section including a plurality of classifier channels, each of the plurality of classifier channels configured, for the interesting objects in the training surveillance video, to output a list of features and their respective likelihoods of occurrences, wherein the list of features is common between all of the plurality of classifier channels; a feature synthesis module connected to the classifier section, the feature synthesis module configured to combine the lists of features from the plurality of classifier channels into a combined list of features; a labeling module configured to apply labels provided by the human operator to the combined list of features and to determine weights of the likelihoods of occurrences; and a training data module connected to the labeling module and receiving the weights; the operational phase mechanism comprises: a detection and tracking module configured to add bounding boxes to interesting objects in an operational surveillance video acquired by the video acquisition mechanism; a classifier section connected to the detection and tracking module, the classifier section including a plurality of classifier channels, each of the plurality of classifier channels configured, for the interesting objects in the operational surveillance video, to output a list of features and their respective likelihoods of occurrences; a feature synthesis module connected to the classifier section, the feature synthesis module configured to combine the lists of features from the plurality of classifier channels into a combined list of features; and a meta-classification module connected to the feature synthesis module and the training data module, the meta-classification module configured to determine labels for the interesting objects in the operational surveillance video using the weights from the training data module and the likelihoods of occurrences of the combined list of features from the feature synthesis module.