18. The method of claim 17 wherein determining whether the image contains a class object includes computing a probability as a function of the similarity score.
17. A method for training and using an object classifier to identify a class object from a captured image, the method comprising the steps of: (a) obtaining a plurality of still images from training data; (b) applying a feature generation technique to the plurality of still images of the training data for identifying candidate features from each respective image; (c) selecting a subset of features from the candidate features using a similarity comparison technique; (d) iteratively repeating steps (a) through (c) a predetermined number of times as a function of the selected subset of features identified in step (c); (e) generating a trained object classifier; (f) capturing an image from an image capture device; (g) classifying features in the captured image using the trained object classifier, wherein classifying the features in the capture image comprises the following steps: identifying image locations in the captured image; comparing each feature of the trained object classifier with each fragment in each image location of the captured image, wherein each fragment in each image location and each feature in the trained object identifier are compared using a feature descriptor technique; computing an appearance descriptor for each fragment in each image location; comparing the appearance descriptor of each fragment in each image location with the appearance descriptor of each feature of the trained object classifier; determining a similarity score between each compared to appearance descriptor of each fragment in each image location and each trained object classifier; and (h) determining whether the captured image contains a class object based on the trained object classifier associating an identified feature in the image with the class object.