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Can Feature Matching using SIFT/SURF be used for classification of similar objects?

For classification of similar objects, I certainly would go for cascade classifiers.

Basically, cascade classifiers is a machine learning method where you train your classifier to detect an object in different images. For it to work well, you need to train your classifier with a lot of positive (where your object is) and negative (where your object is not) images. The method was invented by Viola and Jones in 2001.

There is a ready-made implementation in OpenCV for face detection, you will have a bit more explanations on the openCV documentation (sorry, can't post the link, I'm limited to 1 link for the moment ..)

Now, for the caveats :

  • First, you need a lot of positive and negative images. The more images you have, the better the algorithm will perform. Beware of over-learning : if your training dataset for heels contains, for instance, too many images of a given model it is possible that others will not be detected properly

  • Training the cascade classifier can be long and difficult. The end-result will depend on how well you choose the parameters for training the classifier. Some info on this can be found on this webpage : http://coding-robin.de/2013/07/22/train-your-own-opencv-haar-classifier.html





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