- A method for creating a real-time realistic-looking image of a pair of virtual glasses positioned on a real user face image issued from a real-time camera stream, comprising the following steps: - 100. A face analysis process to estimate, on the real user face image, face parameters comprising the 3D rotation matrix of the user's face, the 3D translation vector of the user's face, morphology parameters of the user's face; - 200. A glasses positioning process associated with a try-on mode for look or real-size simulation that estimate the 3D rotation matrix, the 3D translation vector, and global and local deformation parameters of the virtual glasses, and arms articulation, adapted to the morphology parameters computed in step 100; - 400. A realistic rendering process to mix the real user face image shown on a screen in real-time, with the image of the virtual glasses positioned in step 200, so that the user can see himself on the screen in a mirror-like fashion, characterized in that the user's face is represented by a 3D model based on a mean 3D model g m and parametrized by morphologic parameters α and expression parameters β, and in that the face analysis process 100 comprises a multi-image analysis algorithm refining the estimated face parameters comprising the morphologic parameters α and the expression parameters β of the user's face, wherein it further comprises a step 300 of 3D face tracking algorithm that gives the 3D translation vector of the user's face and 3D rotation matrix of the user's face for each frame by minimizing the 3D face pose parameters β, T and the expression parameters β: min R, T, β proj K × R × g α β + T − p 2 D where R is the 3D rotation matrix, T is the 3D translation, K is the intrinsic camera parameters matrix, p2D is the current position of 3D tracked point in the image and proj is a projection function, the tracked points being pre-defined on the 3D face model, wherein in step 300, a plurality of images with their associated tracked points and estimated parameters β, T and β, called keyframes, are selected in the camera stream, the 3D face tracking algorithm taking into account one of the selected keyframes as the current keyframe used in the tracking process, the current keyframe being the nearest keyframe in terms of parameters distance. - 100. A face analysis process to estimate, on the real user face image, face parameters comprising the 3D rotation matrix of the user's face, the 3D translation vector of the user's face, morphology parameters of the user's face; - 200. A glasses positioning process associated with a try-on mode for look or real-size simulation that estimate the 3D rotation matrix, the 3D translation vector, and global and local deformation parameters of the virtual glasses, and arms articulation, adapted to the morphology parameters computed in step 100; - 400. A realistic rendering process to mix the real user face image shown on a screen in real-time, with the image of the virtual glasses positioned in step 200, so that the user can see himself on the screen in a mirror-like fashion, characterized in that the user's face is represented by a 3D model based on a mean 3D model g m and parametrized by morphologic parameters α and expression parameters β, and in that the face analysis process 100 comprises a multi-image analysis algorithm refining the estimated face parameters comprising the morphologic parameters α and the expression parameters β of the user's face, wherein it further comprises a step 300 of 3D face tracking algorithm that gives the 3D translation vector of the user's face and 3D rotation matrix of the user's face for each frame by minimizing the 3D face pose parameters β, T and the expression parameters β: min R, T, β proj K × R × g α β + T − p 2 D where R is the 3D rotation matrix, T is the 3D translation, K is the intrinsic camera parameters matrix, p2D is the current position of 3D tracked point in the image and proj is a projection function, the tracked points being pre-defined on the 3D face model, wherein in step 300, a plurality of images with their associated tracked points and estimated parameters β, T and β, called keyframes, are selected in the camera stream, the 3D face tracking algorithm taking into account one of the selected keyframes as the current keyframe used in the tracking process, the current keyframe being the nearest keyframe in terms of parameters distance.