Abstract
We present a method for segmenting and estimating the shape of 3-d objects from range data. The technique uses model views, or aspects, to constrain the fitting of deformable models to range data. Based on an initial region segmentation of a range image, regions are grouped into aspects corresponding to the volumetric parts that make up an object. The qualitative segmentation of the range image into a set of volumetric parts not only captures the coarse shape of the parts, but qualitatively encodes the orientation of each part through its aspect. Knowledge of a part's coarse shape, its orientation, as well as the mapping between the faces in its aspect and the surfaces on the part provides strong constraints on the fitting of a deformable model (supporting both global and local deformations) to the data. Unlike previous work in physics-based deformable model recovery from range data, the technique does not require pre-segmented data. Furthermore, occlusion is handled at segmentation time and does not complicate the fitting process, as only 3-D points known to belong to a part participate in the fitting of a model to the part. We present the approach in detail and apply it to the recovery of objects from range data.