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).

Date Published: 26 June 2017
PDF
Proc. SPIE 10334, Automated Visual Inspection and Machine Vision II, 103340E (26 June 2017); doi: 10.1117/12.2264162

Published in SPIE Proceedings Vol. 10334:
Automated Visual Inspection and Machine Vision II
Jürgen Beyerer; Fernando Puente León, Editor(s)