The Active Apearence Models (AAM) are often used in Man-Machine Interaction for their ability to align the faces. We propose a new normalization method for AAM based on distance map in order to strengthen their robustness to differences in illumination. Our normalization do not use the photometric normalization protocol classically used in AAM and is much more simpler to implement. Compared to Distance Map AAM performances of {Leg06} and other AAM implementation which use CLAHE {Zuiderveld94} normalization or gradient information, our proposition is at the same time much robust to illumination and AAM initialization. The tests have been drive in the context of generalization: 10 persons with frontal illumination from M2VTS database {m2vts} were considered to build the AAM, and 17 persons under 21 different illuminations from CMU database {Sim02} were used for the testing base.