  Detection and description of keypoints from an image is a well-studied
problem in Computer Vision. Some methods like SIFT, SURF or ORB are
computationally really efficient. This paper proposes a solution for a
particular case study on object recognition of industrial parts based on
hierarchical classification. Reducing the number of instances leads to better
performance, indeed, that is what the use of the hierarchical classification is
looking for. We demonstrate that this method performs better than using just
one method like ORB, SIFT or FREAK, despite being fairly slower.
