State-of the-art robust 3D watermarking schemes already withstand combinations of a wide variety of attacks (e.g. noise
addition, simplification, smoothing, etc). Nevertheless, there are practical limitations of existing 3D watermarking
methods due to their extreme sensitivity to cropping. Spread Transform Dither Modulation (STDM) method is an
extension of Quantization Index Modulation (QIM). Besides the simplicity and the trade-off between high capacity and
robustness provided by QIM methods, it is also resistant against re-quantization. This paper focuses on two state-of-the-art
techniques which offer different and complementary advantages, respectively QIM-based 3D watermarking and
feature point-based watermarking synchronization. The idea is to combine both in such a way that the new scheme
would benefit from the advantages of both techniques and compensate for their respective fragilities. The resulting
scheme does not make use of the original 3D model in detection but of some parameters as side-information. We show
that robustness against cropping and other common attacks is achieved provided that at least one feature point as well as
its corresponding local neighborhood is retrieved.
Active site prediction, well-known for drug design and medical diagnosis, is a major step in the study and prediction
of interactions between proteins. The specialized literature provides studies of common physicochemical
and geometric properties shared by active sites. Among these properties, this paper focuses on the travel depth
which takes a major part in the binding with other molecules. The travel depth of a point on the protein solvent
excluded surface (SES) can be defined as the shortest path accessible for a solvent molecule between this point
and the protein convex hull.
Existing algorithms providing an estimation of this depth are based on the sampling of a bounding box volume
surrounding the studied protein. These techniques make use of huge amounts of memory and processing time
and result in estimations with precisions that strongly depend on the chosen sampling rate. The contribution of
this paper is a surface-based algorithm that only takes samples of the protein SES into account instead of the
whole volume. We show this technique allows a more accurate prediction, at least 50 times faster.
A validation of this method is also proposed through experiments with a statistical classifier taking as inputs
the travel depth and other physicochemical and geometric measures for active site prediction.
Shape quality assessment is a new challenge for a wide set of 3-D graphics applications and particularly for emerging 3-D watermarking schemes. In order to measure distortions new metrics have to be drawn between an original 3-D surface and its deformed version. These metrics are necessary to determine whether a deformation is perceptually acceptable and therefore whether this deformation should be considered while testing the robustness of a 3-D watermarking scheme. In this paper, we propose an objective metric based on the comparison of 2-D projections of the deformed and original versions of the shape. Rendering conditions are carefully specified as they play a key role on the human perception of the 3-D object. We compare the behaviors of this objective metric and of state-of-the-art metrics to subjective human perception for a set of deformations caused by watermarking schemes and usual watermarking attacks on several 3-D meshes. The protocol of these subjective psychovisual experiments is presented in detail. We discuss these experimental results for the purpose of the benchmarking of 3-D watermarking schemes.
Three-dimensional image quality assessment causes new challenges for a wide set of applications and particularly for emerging 3-D watermarking schemes. First, new metrics have to be drawn for the distortion measurement from an original 3-D surface to its deformed version: this metric is necessary to address distortions that are acceptable and to which a 3-D watermarking algorithm should resist. In this paper, we focus on distortion energy evaluation extending works on distortion minimization for planar and spherical parameterization. Secondly, a key perceptual assessment of 3-D geometrical transforms is their impact on the various 2-D views that can be extracted from the object. As a matter of fact, most of the applications (games, avatars, …) are targeting users owning 2-D screens. In this paper we restrict our study to 3-D shape distortion analysis, assuming standard lighting conditions and we do not address the textures distortion issues. We analyze how to automatically select relevant pairs of 2D projections which needs an initial registration between both shapes to compare. We use a mutual information criterion to assess the distortion for each projection pair and eventually derive a global score by weighting the contributions of each view.
In this paper, we propose a blind watermarking scheme based on automatic feature points detection. The irregular sampling of 3D shapes is a challenging issue for extending well-known signal processing tools. 3D shape watermarking schemes have to resist to common resampling operations used for example in some compression applications. We propose an automatic selection of intrinsic feature points that are robust against surface remeshing. They are detected as multi-scale robust degeneracies of the shape curvature tensor field. The impact of the sampling on the curvature estimation is studied. These points are then used as seeds in the partition of the shape into fast approximated geodesic triangles. Each of them is then remeshed with a regular connectivity and watermarked in the mesh spectral domain. The watermark perturbations computed on the remeshed triangles are the projected on the original points of the 3D object. We discuss the robustness of the feature points and of the overall scheme under various watermarking attacks.
Over the past decade, very fruitful efforts have converged to offer tools devoted to the processing of meshes. Spectral decomposition of mesh geometry has first found its applications in both filtering and mesh partitioning. It has been lately extended to address transmission and watermarking issues. Such a decomposition gives rise to pseudo-frequential information of the geometry defined over the mesh connectivity. For large meshes a piecewise decomposition has to be applied in order to restrict the complexity of the transform.
In this paper, we propose a lapped spectral representation for compression and watermarking purposes.
Due to massive development of 3D meshes exchanges on the Internet, transmission and protection of such data has recently received a special focus. In this paper we present a method to compress and watermark the geometry of a 3D triangle mesh in the mesh spectral domain. We first explain how to improve the quality of the compression using overlapping, then we propose a substitutive watermarking scheme in the mesh spectral domain. Finally, we give an overview of the results obtained both for compression or watermarking. The robustness of the watermarking algorithm against the compression method is demonstrated.