EXTENDING THE POINT DISTRIBUTION MODEL USING POLAR COORDINATES

The Point Distribution Model (PDM) is useful for many tasks involving the location or tracking of deformable objects. However, non-linear va riation must be approximated by a combination of linear variations, re sulting in a non-optimal model which can produce implausible object sh apes. The Polynomial Regression PDM improves on this by allowing polyn omial deformation, but at the cost of computational complexity, and it still fails for objects in which bending or pivoting occurs. We propo se an extension to the PDM which makes selective use of polar coordina tes, and give examples to show that the models produced are often more compact and precise than either of the above methods. We also present two different algorithms for automatically determining pivot position s, and test them on both real and synthetic data.