Let T be a transformation aligning model M with image object O

The pose of object O is its location and orientation, defined by T.

The idea of pose clustering is to compute lots of possible pose

transformations, each based on 2 points from the model and

2 hypothesized corresponding points from the image.

Then cluster all the transformations in pose space and try

to verify the large clusters.