Fast Blended Transformations for Partial Shape Registration

TL;DR

This paper introduces a real-time, multi-shape deformation method that uses a low-dimensional subspace and a dictionary of vertex positions to improve partial shape registration and shape completion.

Contribution

It generalizes skinning transformations to multiple exemplars using a low-dimensional subspace, enabling more accurate and efficient partial shape registration and deformation.

Findings

Supports local-rigid and nearly isometric deformations

Achieves more accurate reconstructions than state-of-the-art models

Enables real-time non-rigid deformation and shape completion

Abstract

Automatic estimation of skinning transformations is a popular way to deform a single reference shape into a new pose by providing a small number of control parameters. We generalize this approach by efficiently enabling the use of multiple exemplar shapes. Using a small set of representative natural poses, we propose to express an unseen appearance by a low-dimensional linear subspace, specified by a redundant dictionary of weighted vertex positions. Minimizing a nonlinear functional that regulates the example manifold, the suggested approach supports local-rigid deformations of articulated objects, as well as nearly isometric embeddings of smooth shapes. A real-time non-rigid deformation system is demonstrated, and a shape completion and partial registration framework is introduced. These applications can recover a target pose and implicit inverse kinematics from a small number of examples and just a few vertex positions. The result reconstruction is more accurate compared to state-of-the-art reduced deformable models.