Fast nonrigid 3D retrieval using modal space transform

Nonrigid or deformable 3D objects are common in many application domains. Retrieval of such objects in large databases based on shape similarity is still a challenging problem. In this paper, we first analyze the advantages of functional operators, and further propose a framework to design novel shape signatures for encoding nonrigid object structures. Our approach constructs a context-aware integral kernel operator on a manifold, then applies modal analysis to map this operator into a low-frequency functional representation, called fast functional transform, and finally computes its spectrum as the shape signature. Our method is fast, isometry-invariant, discriminative, and numerically stable with respect to multiple types of perturbations.