Classifying variable objects using a flexible shape model

Point distribution models (PDMs) are statistical models which represent objects whose shape can vary. A useful feature of PDMs is their ability to capture the shape of variable objects within a training set with a small number of shape parameters. This compact and accurate parametrization can be used for the design of efficient classification systems. The authors describe a classification system which uses shape parameters. They have tested the system on classifying hand outlines, face outlines and hand gestures; experimental results are presented.<
>