Part-based 3D descriptions of complex objects from a single image

Volumetric, 3D, part-based descriptions of complex objects in a scene can be highly beneficial for many tasks such as generic object recognition, navigation, and manipulation. However, it has been difficult to derive such descriptions from image data. There has been some progress in getting such descriptions from range data or from perfect contours, but analysis of a real intensity image presents many difficulties. The object and part boundaries do not completely correspond to image boundaries. The detected boundaries are often fragmented and many boundaries due to surface markings, shadows, and noise are present. In addition, inference of 3D from a 2D image is difficult. The paper describes a method to compute the desired descriptions from a single image by exploiting projective properties of a class of generalized cylinders and of possible joints between them. Experimental results on some examples are given