3D Piecewise Planar Object Model for Robotics Manipulation

Man-made environments are abundant with pla- nar surfaces which have attractive properties for robotics manipulation tasks and are a prerequisite for a variety of vision tasks. This work presents automatic on-line 3D object model ac- quisition assuming a robot to manipulate the object. Objects are represented with piecewise planar surfaces in a spatio-temporal graph. Planes once detected as homographies are tracked and serve as priors in subsequent images. After reconstruction of the planes the 3D motion is analyzed and initial object hypotheses are created. In case planes start moving independently a split event is triggered, the spatio-temporal object graph is traced back and visible planes as well as occluded planes are assigned to the most probable split object. The novelty of this framework is to formalize Multi-body Structure-and-Motion (MSaM), that is, to segment interest point tracks into different rigid objects and compute the multiple-view geometry of each object, with Minimal Description Length (MDL) based on model selection of planes in an incremental manner. Thus, object models are built from planes, which directly can be used for robotic manipulation.