Using spatial sorting and ranking in model-based object recognition

A new method has been developed for overcoming some of the major obstacles of object recognition. It represents both 2D images and 3D models from a database by view-point invariant descriptors in the same invariant space. As there is a large number of possible matches between the image and model invariants, there is a crucial need to perform this match efficiently. We answer this need by using an adaptation of spatial sorting based on the octree representation of the model points and image lines in three-dimensional space. We show the advantage of the octree method over the traditional “brute-force” approach and we compare the merits of the two methods. This makes it possible for the recognition task to be performed in a reasonable time for a large number of models.