Basic Algorithm for Image Classification I have been trying to implement image classification by extracting facial features. I tried starting with some already established methods like Multi Kernel Approach, using Independent Component Analysis etc. Is there a very basic algorithm for image classification with which I can proceed the implementation ? 

The data set I am currently considering is CMU Face Images data set. So aim is to separate images with human faces to those who do not contain human faces. I think I need to learn parameters by supplying  positive data set and negative data set as well. I am aware that SIFT, SURF, VJ algorithm etc. are helpful fir extracting features from an image. But I am stuck on how to start i.e. what features are required for face detection, and how to proceed towards implementing them.
Have a look at this report by Marques (PDF). In particular, have a read through section 1.4. It describes several different aspects to the face detection problem. You might want to decide what scenario you're after. Fully unconstrained (uncontrolled environment) face detection is hard to do accurately.

As a first approach, try just doing color-based segmentation.  See this paper by Singh, Chauhan, Vatsa and Singh for some details about how to use color to segment your images for face detection.