I would have loved to make the first noise because my current work on face modeling has made me a big fan of feature based method. It is nearly impossible to do dense stereo matching in surfaces as smooth as the face unless we are using active vision ( like projecting patterns ). Almost all methods of dense stereo fail to recover a different depth value for the nose.

I think there is a flaw in the reasoning given in direct method paper. They say in page three, start of para 3

" In other words, the direct method use information from all pixels, weighting the contribution of each pixel according to the underlying image structure around the pixel"

Now it is clear from the above statement that the pixels in smooth regions ( where we can't detect corners ) are unreliable and are automatically given less weight. Are they not contradicting their own statement that they use all pixels instead of a selected few. They are using all pixels but only a selected few dominate the result.

Furthermore I think it is very difficult(impossible??) to do wide baseline stereo using direct method.

However I do feel that direct methods should be applied in situations where we have very dense sampling for the space .. for example a video sequence..