Study on assembly part recognition using part-based superquadric model

Abstract

This paper presents a new volumetric approach to 3D object recognition by using PBSM (Part-Based Superquadric Model). The assembly part object usually can be constructed with the set of volumetric primitives and the relationships of them. We describe volumetric properties of the model object with superquadric parameters. In addition, our model base has the relationships of volumetric primitives as well as the surface information: the surface type, the junction type between neighboring surfaces. These surface attributes and relationships of volumetrics are effectively used in recognition process. Our integrated method is robust to recognition of the identity, position, and orientation of randomly oriented assembly parts. Furthermore, we can reduce the effects of self-occlusion and non-linear shape changes according to the viewpoint.