International Journal of Engineering and Technology

We present a new model for reading face images and image sequences using Graceful Labeling Active Appearance Model (GLAAM). The GLAAM contains a statistical, photo-realistic model of the chassis and grey-level appearance of faces. This paper demonstrates the use of the GLAAM’s ef?cient iterative matching scheme for image interpretation. We use the GLAAM as a basis for face identification, obtain good results for dif?cult images. We show how the GLAAM framework allows identity information to be decoupled from other variation, allowing evidence of identity to be integrated over a sequence. The GLAAM approach makes optimal use of the evidence from either a single image or image sequence. Since we derive a complete description of a given image our method can be used as the basis for a range of face image interpretation tasks.