Mutual Information-Based 3D Surface Matching with Applications to Face Recognition and Brain Mapping

Face recognition and many medical imaging applications require the computation of dense correspondence vector fields that match one surface with another. In brain imaging, surface-based registration is useful for tracking brain change, and for creating statistical shape models of anatomy. Based on surface correspondences, metrics can also be designed to measure differences in facial geometry and expressions. To avoid the need for a large set of manually-defined landmarks to constrain these surface correspondences, we developed an algorithm to automate the matching of surface features. It extends the mutual information method to automatically match general 3D surfaces (including surfaces with a branching topology). We use diffeomorphic flows to optimally align the Riemann surface structures of two surfaces. First, we use holomorphic 1forms to induce consistent conformal grids on both surfaces. High genus surfaces are mapped to a set of rectangles in the Euclidean plane, and closed g...

• Type: Conference
• Year: 2005
• Where: ICCV
• Authors: Yalin Wang, Ming-Chang Chiang, Paul M. Thompson
• Keywords: Computer Vision, ICCV 2005, Surface Correspondences, Surface Features, Surfaces