Active Shape Models and the Shape Approximation Problem

The Active Shape Model(ASM) is an iterative algorithm for image interpretation based upon a Point Distribution Model. Each iteration of the ASM has two steps: Image data interrogation followed by shape approximation. Here we consider the shape approximation step in detail. We present a new method of shape approximation which uses directional constraints. We show how the error term for the shape approximation problem can be extended to cope with directional constraints and present iterative solutions to the 2D and 3D problems. We also show how the error term can be modified to allow a closed solution in the 2D case.