3d Object Understanding From 2d Images

This paper deals with 3D object understanding from 2D images, including articulated objects in active vision environment, Usually an articulated object is divided into two portions: main rigid portion and articulated portion. It is more complicated than "rigid" object in that the relative positions, shaprs or angles between the main portion and the articulated portion have essentially infinite variations, in addition to the infinite variations of each individual rigid portions due to orientations, rotations and topological transformations. A new method generalized from linear combination is employed to investigate such problems. It uses very few learning samples, and can describe, understand, and recognize 3D articulated objects while the objects status is being changed in an active vision environment.