Automatic deformation transfer for data-driven haptic rendering

Abstract

This paper addresses a major challenge in data-driven haptic modeling of deformable objects. Data-driven modeling is done for specific objects and is difficult to generalize for nearly isometric objects that have similarities in semantics or topology. This limitation prevents the wide use of the data-driven modeling techniques when compared with parametric methods such as finite element methods. The proposed solution is to incorporate deformation transfer methods when processing similar instances. The contributions of this work are focused on the novel automatic shape correspondence method that overcomes the problems of symmetry and semantics presence requirement. The results shows that the proposed algorithm can efficiently calculate the correspondence and transfer deformations for a range of similar 3D objects.