3D articulated object recognition: a case study

A simple method for visualizing, understanding, interpreting, and recognizing 3D objects from 2D images is presented. It extended the linear combination methods, uses parallel pattern matching and can handle 3D rigid concave objects as well as convex objects, yet, needs only a very small number of learning samples. Some real images are illustrated, with future research discussed including more complicated images such as 3D concave and articulated objects.