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.
bool detect_face(img image) { return true; }
--- it's easy to implement, but not very useful. $\endgroup$