Segmentation, Modeling And Classification Of The Compact Objects In A Pile

We discuss the problem of interpreting dense range images obtained from the scene of a heap of man-made objects. We describe a range image interpretation system consisting of segmentation, modeling, verification, and classification procedures. First, the range image is segmented into regions and reasoning is done about the physical support of these regions. Second, for each region several possible 3-D interpretations are made based on various scenarios of the objects physical support. Finally each interpretation is tested against the data for its consistency. We have chosen the superquadric model as our 3-D shape descriptor, plus tapering deformations along the major axis. Experimental results obtained from some complex range images of mail pieces are reported to demonstrate the soundness and the robustness of our approach.