A computer-implemented method for designing a 3D modeled object representing a real object, comprising the steps of: • providing a 3D mesh representing the real object and having vertices, a texturing image and a mapping between the vertices of the 3D mesh and pixels of the texturing image; then • maximizing a probability P ( L) of the form: P L V = 1 Z exp − ∑ i = 1 n φ i ′ L v i − ∑ f ∈ F ψ f ′ L v i i ∈ f where: ▪ n designates the number of vertices of the 3D mesh and v i designates the vertices of the 3D mesh, ▪ L ( v i) designates a pixel shift to be applied after mapping vertex v i on the texturing image and selected in a predetermined finite set, ▪ Z = ∑ L V exp − ∑ i = 1 n φ i ′ L v i − ∑ f ∈ F ψ f ′ L v i i ∈ f, ▪ designates the set of sets of indices of mesh tiles of the 3D mesh, ▪ φ i ′ designates a cost function associated to vertex v i and decreasingly depending on an extent to which the result of applying the pixel shift to vertex v i once projected onto the texturing image according to the mapping, after mapping vertex v i on the texturing image respects a predetermined relation between vertices of the 3D mesh and pixels of the texturing image, the predetermined relation being a predetermined knowledge that geometrical features of the 3D mesh should correspond to graphical features of the texturing image, ▪ ψ f ′ designates a cost function associated to a tile f of the 3D mesh and depending on a global difference between pixel shifts selected for the vertices of tile f, the optimization thereby tending in the exploration of the argument solution to reach pixel shifts that are the same for all vertices of each respective single tile f, wherein the step of maximizing is performed with a predetermined discrete Markov Random Field optimization scheme viewing the 3D mesh and the pixel shifts associated to the texture coordinates of the vertices of the 3D mesh as a Markov Random Field of energy: − log P L V − log Z = ∑ i = 1 n φ i ′ L v i + ∑ f ∈ F ψ f ′ L v i i ∈ f); and • texturing the 3D mesh according to the texturing image, to the mapping, and to the result of the step of maximizing. • providing a 3D mesh representing the real object and having vertices, a texturing image and a mapping between the vertices of the 3D mesh and pixels of the texturing image; then • maximizing a probability P ( L) of the form: P L V = 1 Z exp − ∑ i = 1 n φ i ′ L v i − ∑ f ∈ F ψ f ′ L v i i ∈ f where: ▪ n designates the number of vertices of the 3D mesh and v i designates the vertices of the 3D mesh, ▪ L ( v i) designates a pixel shift to be applied after mapping vertex v i on the texturing image and selected in a predetermined finite set, ▪ Z = ∑ L V exp − ∑ i = 1 n φ i ′ L v i − ∑ f ∈ F ψ f ′ L v i i ∈ f, ▪ designates the set of sets of indices of mesh tiles of the 3D mesh, ▪ φ i ′ designates a cost function associated to vertex v i and decreasingly depending on an extent to which the result of applying the pixel shift to vertex v i once projected onto the texturing image according to the mapping, after mapping vertex v i on the texturing image respects a predetermined relation between vertices of the 3D mesh and pixels of the texturing image, the predetermined relation being a predetermined knowledge that geometrical features of the 3D mesh should correspond to graphical features of the texturing image, ▪ ψ f ′ designates a cost function associated to a tile f of the 3D mesh and depending on a global difference between pixel shifts selected for the vertices of tile f, the optimization thereby tending in the exploration of the argument solution to reach pixel shifts that are the same for all vertices of each respective single tile f, wherein the step of maximizing is performed with a predetermined discrete Markov Random Field optimization scheme viewing the 3D mesh and the pixel shifts associated to the texture coordinates of the vertices of the 3D mesh as a Markov Random Field of energy: − log P L V − log Z = ∑ i = 1 n φ i ′ L v i + ∑ f ∈ F ψ f ′ L v i i ∈ f); and ▪ n designates the number of vertices of the 3D mesh and v i designates the vertices of the 3D mesh, ▪ L ( v i) designates a pixel shift to be applied after mapping vertex v i on the texturing image and selected in a predetermined finite set, ▪ Z = ∑ L V exp − ∑ i = 1 n φ i ′ L v i − ∑ f ∈ F ψ f ′ L v i i ∈ f, ▪ designates the set of sets of indices of mesh tiles of the 3D mesh, ▪ φ i ′ designates a cost function associated to vertex v i and decreasingly depending on an extent to which the result of applying the pixel shift to vertex v i once projected onto the texturing image according to the mapping, after mapping vertex v i on the texturing image respects a predetermined relation between vertices of the 3D mesh and pixels of the texturing image, the predetermined relation being a predetermined knowledge that geometrical features of the 3D mesh should correspond to graphical features of the texturing image, ▪ ψ f ′ designates a cost function associated to a tile f of the 3D mesh and depending on a global difference between pixel shifts selected for the vertices of tile f, the optimization thereby tending in the exploration of the argument solution to reach pixel shifts that are the same for all vertices of each respective single tile f, • texturing the 3D mesh according to the texturing image, to the mapping, and to the result of the step of maximizing.