3D object indexing and recognition

In this paper, we address the problem of 3D object recognition from a single 2D image using models database. We propose a method based on geometric quasi-invariant features of the 2D images. We index the 2D images in a model base using a modified quad-tree technique that enhance the research process. The final vote that matches the 2D object image to the 3D object of the database is solved by a vector approximation file which overcomes the difficulties of high dimensionality by following not the data partitioning approach of conventional index methods, but rather as filter based approach.