A direct part-level segmentation of range images using volumetric models

Volumetric part models play an important part in robotic applications such as grasping, path planning, object avoidance, and modeling kinematic chains. The authors present a novel method for reliable and efficient recovery of part-descriptions in terms of superquadric models from range images. In contrast to usual approaches which perform the recovery of volumetric models in several steps (from curves, surfaces to volumes), the authors show that a direct recovery is possible. This is achieved by combining two existing methods: recover-and-select paradigm and recovery of superquadric models. A redundant set of superquadratics is initiated in the image and only the recovered models resulting in the simplest overall description are selected. The author show the results on several real range images