Motion-based mesh segmentation using augmented silhouettes

Motion-based segmentation, the problem of detecting rigid parts of an articulated three-dimensional shape, is an open challenge that has several applications in mesh animation, compression, and interpolation. We present a novel approach that uses the visual perception of the shape and its motion to distinguish the rigid from the deformable parts of the object. Using two-dimensional projections of the different shape poses with respect to a number of different view points, we derive a set of one-dimensional curves, which form a superset of the mesh silhouettes. Analysing these augmented silhouettes, we identify the vertices of the mesh that correspond to the deformable parts, and a subsequent clustering approach, which is based on the diffusion distance, yields a motion-based segmentation of the shape.

► We propose a novel approach for motion-based mesh segmentation. ► We capture different silhouettes of a deforming model from various viewpoints. ► The analysis of the silhouettes allows us to understand the structure of the object itself. ► This greatly reduces the complexity of the problem. ► Our technique is faster than the state-of-the-art with comparable results.