A Multi-View Nonlinear Active Shape Model Using Kernel PCA

This work introduces a multi-view nonlinear shape model utilising 2D view-dependent constraint without explicit reference to 3D structures, and adopts Kernel PCA based on Support Vector Machines.

Abstract

Recovering the shape of any 3D object using multiple 2D views requires establishing correspondence between feature points at different views. How-ever changes in viewpoint introduce self-occlusions, resulting nonlinear vari-ations in the shape and inconsistent 2D features between views. Here we introduce a multi-view nonlinear shape model utilising 2D view-dependent constraint without explicit reference to 3D structures. For nonlinear model transformation, we adopt Kernel PCA based on Support Vector Machines. 1