Blind watermarking of 3D meshes using robust feature points detection

We present a new blind robust watermarking scheme for 3D meshes. Feature points are used to build a partition of the mesh shape that resists to common 3D watermarking attacks. These points are automatically selected through a multi-scale estimation of the curvature tensor field. The automatic capture of robust feature points and its use for blind detection in a robust watermarking scheme are the contribution of this paper. Our watermarking scheme proceeds by first partitioning the mesh shape using a geodesic Delaunay triangulation of the detected feature points. Each of these geodesic triangle patches is then parameterized and remeshed by a subdivision strategy to obtain a robust base meshing. Then remeshed patches are watermarked in the spectral domain and original mesh points are finally projected on the corresponding watermarked patches. This strategy shows good preliminary results as it resists to affine transforms, white noise addition, smoothing, crop and sampling changes such as decimation, subdivision or remeshing.