Full volumetric descriptions from three intensity images

We address the problem of recovering high-level, volumetric and segmented (or part-based) descriptions of objects from intensity images. As input we use three closely spaced images of an object and recover descriptions based on generalized cylinders (GCs). We start by extracting a hierarchy of groups from contour images in the three views. Grouping is based on proximity, parallelism, and symmetry. The groups in the three views are matched and their contours are labeled as "true" edges. We then infer the GC axis, its cross-section, and the scaling function. The cross-section is recovered if seen in the images, else it is inferred using the visible surfaces and GC properties. We consider groups with true edges, limb edges, or a combination of both. The coarse volumetric descriptions obtained are refined to include surface details as seen in the intensity images. We demonstrate results on real images of moderately complex objects with texture and shadows.