1. A method for adapting a classifier to detect an object in a particular scene, wherein the particular scene was unknown when the classifier was trained with training data, comprising the steps of: acquiring a video of frames of the particular scene with a camera; constructing a model of the particular scene model using the frames in the video; applying the classifier to the model to select negative examples; adding a subset of the new negative examples to the training data while removing another set of existing negative examples from the training data based on an uncertainty measure; adding selected positive examples to the training data; retraining the classifier; and repeating the adding and retraining steps until a desired accuracy level is reached to obtain a scene specific classifier.