I followed the project until the end (http://www.codeproject.com/Articles/6...). I would like to know how to use the end descriptor to classify the image. How do I know how similar is this descriptor in comparison to the previous training images or dictionary?
Typically you train a multi-class classifier (or multiple one-vs-rest or one-vs-one classifiers). The classifier then predicts the correct class acoording to the training BoW-features. You can get a way of "similarity" measure if you either choose a classifier which gives you probabilities right away or you compute probabilities from the classifier outputs, e.g. if you used SVMs you could get probabilities from the decision function via Platt calibration.
Asked: May 7 '15
Seen: 304 times
Last updated: May 08 '15
