Métriques de distorsion pour l'analyse comparative de schémas de filigranage 3D

Dans cet article, nous traitons de la problématique de la mesure de distorsion des maillages 3D dans le cadre de l'analyse comparative de schémas de filigranage. Cette mesure est nécessaire afin de classifier les types de déformations acceptables et de déterminer des seuils de tolérance. Nous proposons dans cette optique deux approches distinctes et complémentaires. La première consiste en une métrique perceptive globale basée sur l'analyse des différences entre les vues 2D correspondantes de l'objet 3D et de sa version déformée. Nous montrons par nos résultats que le choix de l'information mutuelle comme critère de comparaison de ces vues projetées permet de mieux détecter de faibles distorsions à la limite de l'imperceptibilité, courantes dans le cadre du filigranage. La deuxième approche complète la première en analysant les différences locales entre maillages via l'estimation de l'énergie de déformation. Cette stratégie trouve ses fondements notamment dans le calcul de la paramétrisation planaire ou sphérique des surfaces maillées. Cette étude se conclut par la comparaison des résultats de ces méthodes et des métriques 3D de l'état de l'art

HTTP/2-based adaptive streaming of HEVC video over 4G/LTE networks

In HTTP Adaptive Streaming, video content is temporally divided into multiple segments, each encoded at several quality levels. The client can adapt the requested video quality to network changes, generally resulting in a smoother playback. Unfortunately, live streaming solutions still often suffer from playout freezes and a large end-to-end delay. By reducing the segment duration, the client can use a smaller temporal buffer and respond even faster to network changes. However, since segments are requested subsequently, this approach is susceptible to high round-trip times. In this letter, we discuss the merits of an HTTP/2 push-based approach. We present the details of a measurement study on the available bandwidth in real 4G/LTE networks, and analyze the induced bit-rate overhead for HEVC-encoded video segments with a sub-second duration. Through an extensive evaluation with the generated video content, we show that the proposed approach results in a higher video quality (+7.5%) and a lower freeze time (-50.4%), and allows to reduce the live delay compared with traditional solutions over HTTP/1.1

Perception and re-synchronization issues for the watermarking of 3D shapes

Digital watermarking is the art of embedding secret messages in multimedia contents in order to protect their intellectual property. While the watermarking of image, audio and video is reaching maturity, the watermarking of 3D virtual objects is still a technology in its infancy. In this thesis, we focus on two main issues. The first one is the perception of the distortions caused by the watermarking process or by attacks on the surface of a 3D model. The second one concerns the development of techniques able to retrieve a watermark without the availability of the original data and after common manipulations and attacks. Since imperceptibility is a strong requirement, assessing the visual perception of the distortions that a 3D model undergoes in the watermarking pipeline is a key issue. In this thesis, we propose an image-based metric that relies on the comparison of 2D views with a Mutual Information criterion. A psychovisual experiment has validated the results of this metric for the most common watermarking attacks. The other issue this thesis deals with is the blind and robust watermarking of 3D shapes. In this context, three different watermarking schemes are proposed. These schemes differ by the classes of 3D watermarking attacks they are able to resist to. The first scheme is based on the extension of spectral decomposition to 3D models. This approach leads to robustness against imperceptible geometric deformations. The weakness of this technique is mainly related to resampling or cropping attacks. The second scheme extends the first to resampling by making use of the automatic multiscale detection of robust umbilical points. The third scheme then addresses the cropping attack by detecting robust prong feature points to locally embed a watermark in the spatial domain.(FSA 3)--UCL, 200

From 3D Mesh Data Hiding to 3D Shape Blind

The need for secure communication of high value 3D virtual objects is becoming very important as a consequence of an increasing activity in simulation, entertainment, industrial design and cultural heritage. Secure communications of intangibles rely on cryptography and on watermarking of the transmitted objects to protect them against modifications (authentication watermarks) and redistributions (tracing forensic watermarks). While watermarking of image, audio and video is reaching maturity, 3D watermarking is still a technology in its infancy. Up to now, 3D watermarking has mainly focused on triangle meshes which are the most used digital representations of the shape of a 3D model. We show in this paper how recent signal processing techniques applied to meshes pave the way towards blind and robust watermarking of 3D shapes. We propose a survey of existing techniques and discuss their robustness, imperceptibility, capacity and security constraints

Blind and Robust Watermarking of 3D Models: How to Withstand the Cropping Attack?

International audienceState-of-the-art blind and robust 3D watermarking schemes already resist against combinations of a wide variety of at- tacks (e.g. noise addition, simplification, smoothing, ...) ex- cept the cropping attack. This attack is however very common and should be dealt with in a copyright protection framework. In this paper, we propose a technique which enables to extend the robustness of such schemes to cropping. Our algorithm proceeds by the automatic detection of robust shape feature points which are then used for the embedding of a watermark in a local neighborhood. 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 are retrieved

Université catholique de Louvain Communication and Remote Sensing Lab.

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 then 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

T-FLASH: TENSOR VISUALIZATION IN MEDICAL STUDIO

Tensor valued data are frequently used in medical imaging. For a 3-dimensional second order tensor such data imply at least six degrees of freedom for each voxel. The operators ability to perceive this information is of outmost importance and in many cases a limiting factor for the interpretation of the data. In this paper we propose a decomposition of such tensor fields using the Tflash tensor glyphs that intuitively conveys important tensor features to a human observer. A matlab implementation for visualization of single tensors are described in detail and a VTK/ITK implementation for visualization of tensor fields have been developed as a Medical Studio componen

Fast surface-based travel depth estimation algorithm for macromolecule surface shape description.

Travel Depth, introduced by Coleman and Sharp in 2006, is a physical interpretation of molecular depth, a term frequently used to describe the shape of a molecular active site or binding site. Travel Depth can be seen as the physical distance a solvent molecule would have to travel from a point of the surface, i.e., the Solvent-Excluded Surface (SES), to its convex hull. Existing algorithms providing an estimation of the Travel Depth are based on a regular sampling of the molecule volume and the use of the Dijkstra's shortest path algorithm. Since Travel Depth is only defined on the molecular surface, this volume-based approach is characterized by a large computational complexity due to the processing of unnecessary samples lying inside or outside the molecule. In this paper, we propose a surface-based approach that restricts the processing to data defined on the SES. This algorithm significantly reduces the complexity of Travel Depth estimation and makes possible the analysis of large macromolecule surface shape description with high resolution. Experimental results show that compared to existing methods, the proposed algorithm achieves accurate estimations with considerably reduced processing times