We present a practical algorithm for computing robust, multiscale curve and surface skeletons of 3D objects. Based on a model which follows an advection principle, we assign to each point on the skeleton a part of the object surface, called the collapse. The size of the collapse is used as a uniform importance measure for the curve and surface skeleton, so that both can be simplified by imposing a single threshold on this intuitive measure. The simplified skeletons are connected by default, without special precautions, due to the monotonicity of the importance measure. The skeletons possess additional desirable properties: They are centered, robust to noise, hierarchical, and provide a natural skeleton-to-boundary mapping. We present a voxel-based algorithm that is straightforward to implement and simple to use. We illustrate our method on several realistic 3D objects.

We present a practical algorithm for computing robust, multiscale curve and surface skeletons of 3D objects. Based on a model which follows an advection principle, we assign to each point on the skeleton a part of the object surface, called the collapse. The size of the collapse is used as a uniform importance measure for the curve and surface skeleton, so that both can be simplified by imposing a single threshold on this intuitive measure. The simplified skeletons are connected by default, without special precautions, due to the monotonicity of the importance measure. The skeletons possess additional desirable properties: They are centered, robust to noise, hierarchical, and provide a natural skeleton-to-boundary mapping. We present a voxel-based algorithm that is straightforward to implement and simple to use. We illustrate our method on several realistic 3D objects.

We present an effective framework for segmenting 3D shapes into meaningful components using the curve skeleton. Our algorithm identifies a number of critical points on the curve skeleton, either fully automatically as the junctions of the curve skeleton, or based on user input. We use these points to construct a partitioning of the object surface using geodesics. Because it is based on the curve skeleton, our segmentation intrinsically reflects the shape symmetry and topology. By using geodesics we obtain segments that have smooth, minimally twisting borders. Finally, we present a hierarchical segmentation of shapes which reflects the hierarchical structure of the curve skeleton. We describe a voxel-based implementation of our method which is robust and noise resistant, computationally efficient, able to handle shapes of complex topology, and which delivers levelof-detail segmentations. We demonstrate the framework on various real-world 3D shapes.

We present a part-type segmentation method for articulated voxel-shapes based on curve skeletons. Shapes are considered to consist of several simpler, intersecting shapes. Our method is based on the junction rule: the observation that two intersecting shapes generate an additional junction in their joined curve-skeleton near the place of intersection. For each curve-skeleton point, we construct a piecewise-geodesic loop on the shape surface. Starting from the junctions, we search along the curve skeleton for points whose associated loops make for suitable part cuts. The segmentations are robust to noise and discretization artifacts, because the curve skeletonization incorporates a single user-parameter to filter spurious curve-skeleton branches. Furthermore, segment borders are smooth and minimally twisting by construction. We demonstrate our method on several real-world examples and compare it to existing part-type segmentation methods.