This paper presents a method for face identification using an eigenfaces approach. Our technique is suitable for use within ambient security environments and is robust across variations in pose, expression and illuminations conditions. To account for these variations, we use a face template matching algorithm based on a 3D head model. Thanks to our tracking-based approach our algorithm is able to extract simultaneously all parameters related to the face expression and to the 3D posture. With these estimates, we are able to reconstruct a frontal, neutral and normalized image on which an eigenface classification for identification is performed. (6 pages)