1. A face recognition method comprising: obtaining an original face image from a database and reconstructing a 3D face model for said original face image using a 3D morphable face model; providing synthesized face images from said 3D face model for training a face recognition classifier; receiving a plurality of video frames of a face, and obtaining a similarity probability for each said video frame from said face recognition classifier; and fusing said similarity probability for each said video frame by accumulation to obtain a face recognition confidence value, and if said face recognition confidence value is larger than a threshold, said face is recognized to be the same as the face from said original face image.
8. The face recognition method according to claim 1 , wherein the step for obtaining said face recognition confidence value by fusing said temporal similarity probability of each said video frame by accumulation is: P i t = ( ω × P i t - 1 + ( 1 - ω ) × P i t , SVC ) ∑ i ⁢ ( ω × P i t - 1 + ( 1 - ω ) × P i t , SVC ) , i = 1 , 2 , … ⁢ , n , wherein ω is a forgetting factor, P i t,SVC is a posterior probability, denoting the probability that a single video frame belongs to the i th class at time t, and P i t,SVC is merged with previously accumulated probability P i t−1 to contribute to the final similarity probability P i t accumulated up to time t.