Shape Registration in Implicit Spaces Using Information Theory and Free Form Deformations

We present a novel variational and statistical approach for shape registration. Shapes of interest are implicitly embedded in a higher dimensional space of distance transforms. In this implicit embedding space, registration is formulated in a hierarchical manner: the Mutual Information criterion supports various transformation models and is optimized to perform global registration; then a B-spline based Incremental Free Form Deformations (IFFD) model is used to minimize a Sum-of-Squared-Differences (SSD) measure and further recover a dense local nonrigid registration field. The key advantage of such framework is twofold: (1) it naturally deals with shapes of arbitrary dimension (2D, 3D or higher) and arbitrary topology (multiple parts, closed/open), and (2) it preserves shape topology during local deformation, and produces local registration fields that are smooth, continuous and establish one-to-one correspondences. Its invariance to initial conditions is evaluated through empirical ...

• Type: Journal
• Year: 2006
• Where: PAMI
• Authors: Xiaolei Huang, Nikos Paragios, Dimitris N. Metaxas
• Keywords: Local Nonrigid Registration, PAMI 2006, Registration Fields, Shape Registration