Posts tagged with: representation learning

How does Feature Extraction work on Images?

Here I share enhanced version of one of my Quora answer to a similar question …

There is no single answer for this question since there are many diverse set of methods to extract feature from an image.

First, what is called feature? “a distinctive attribute or aspect of something.” so the thing is to have some set of values for a particular instance that diverse that instance from the counterparts. In the field of images, features might be raw pixels for simple problems like digit recognition of well-known Mnist dataset. However, in natural images, usage of simple image pixels are not descriptive enough. Instead there are two main steam to follow. One is to use hand engineered feature extraction methods (e.g. SIFT, VLAD, HOG, GIST, LBP) and the another stream is to learn features that are discriminative in the given context (i.e. Sparse Coding, Auto Encoders, Restricted Boltzmann Machines, PCA, ICA, K-means). Note that second alternative, Continue Reading

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