Study of landmarks estimation stability produced by AAM

摘要

Active Appearance Model (AAM) is an accurate and robust tool and is suitable when it's needed to estimate shape of object when its' approximate shape is known but varies within a certain range from instance to instance. An AAM allows complex models of shape (for example human face) and appearance to be matched to new images rapidly. An AAM contains a statistical model of the shape and gray level or color appearance of an object of interest. The associated search algorithm exploits the locally linear relationship between model parameter displacements and the residual errors between model instance and image. AAM is widely used but the research of its' accuracy and stability still remains an important and not fully learned issue. In this paper, we study landmarks stability and error estimation produced by AAM in different lightning conditions and signal-to-noise ratio (SNR).