With detected keypoints across images, correspondences/matches between test image and models can be found by comparing their descriptors.

Then direct voting is used to choose the best model.

In addition to accuracy, efficiency is another problem. Virtually keypoints of test image need to be compared with every keypoints of models if no approximation is used. The situation gets worse when dealing with large database.

To address the problem, we proposed a Hierarchical Building Recognition scheme.