3-D Mesh geometry compression with set partitioning in the spectral domain

This paper explains the development of a highly efficient progressive 3-D mesh geometry coder based on the region adaptive transform in the spectral mesh compression method. A hierarchical set partitioning technique, originally proposed for the efficient compression of wavelet transform coefficients in high-performance wavelet-based image coding methods, is proposed for the efficient compression of the coefficients of this transform. Experiments confirm that the proposed coder employing such a region adaptive transform has a high compression performance rarely achieved by other state of the art 3-D mesh geometry compression algorithms. A new, high-performance fixed spectral basis method is also proposed for reducing the computational complexity of the transform. Many-to-one mappings are employed to relate the coded irregular mesh region to a regular mesh whose basis is used. To prevent loss of compression performance due to the low-pass nature of such mappings, transitions are made from transform-based coding to spatial coding on a per region basis at high coding rates. Experimental results show the performance advantage of the newly proposed fixed spectral basis method over the original fixed spectral basis method in the literature that employs one-to-one mappings.This work was supported in part by the Scientific and Technological Research Council of Turkey, and conducted under Project 106E064Publisher's Versio

JPEG2000-Based Data Hiding to Synchronously Unify Disparate Facial Data for Scalable 3D Visualization

International audienceWe present a scalable encoding strategy for the 3D facial data in various bandwidth scenarios. The scalability, needed to cater diverse clients, is achieved through the multiresolution characteristic of JPEG2000. The disparate 3D facial data is synchronously unified by the application of data hiding wherein the 2.5D facial model is embedded in the corresponding 2D texture in the discrete wavelet transform (DWT) domain. The unified file conforms to the JPEG2000 standard and thus no novel format is introduced. The method is effective and has the potential to be applied in videosurveillance and videoconference applications

Representation and coding of 3D video data

Livrable D4.1 du projet ANR PERSEECe rapport a été réalisé dans le cadre du projet ANR PERSEE (n° ANR-09-BLAN-0170). Exactement il correspond au livrable D4.1 du projet

Parallel Mesh Processing

Die aktuelle Forschung im Bereich der Computergrafik versucht den zunehmenden Ansprüchen der Anwender gerecht zu werden und erzeugt immer realistischer wirkende Bilder. Dementsprechend werden die Szenen und Verfahren, die zur Darstellung der Bilder genutzt werden, immer komplexer. So eine Entwicklung ist unweigerlich mit der Steigerung der erforderlichen Rechenleistung verbunden, da die Modelle, aus denen eine Szene besteht, aus Milliarden von Polygonen bestehen können und in Echtzeit dargestellt werden müssen. Die realistische Bilddarstellung ruht auf drei Säulen: Modelle, Materialien und Beleuchtung. Heutzutage gibt es einige Verfahren für effiziente und realistische Approximation der globalen Beleuchtung. Genauso existieren Algorithmen zur Erstellung von realistischen Materialien. Es gibt zwar auch Verfahren für das Rendering von Modellen in Echtzeit, diese funktionieren aber meist nur für Szenen mittlerer Komplexität und scheitern bei sehr komplexen Szenen. Die Modelle bilden die Grundlage einer Szene; deren Optimierung hat unmittelbare Auswirkungen auf die Effizienz der Verfahren zur Materialdarstellung und Beleuchtung, so dass erst eine optimierte Modellrepräsentation eine Echtzeitdarstellung ermöglicht. Viele der in der Computergrafik verwendeten Modelle werden mit Hilfe der Dreiecksnetze repräsentiert. Das darin enthaltende Datenvolumen ist enorm, um letztlich den Detailreichtum der jeweiligen Objekte darstellen bzw. den wachsenden Realitätsanspruch bewältigen zu können. Das Rendern von komplexen, aus Millionen von Dreiecken bestehenden Modellen stellt selbst für moderne Grafikkarten eine große Herausforderung dar. Daher ist es insbesondere für die Echtzeitsimulationen notwendig, effiziente Algorithmen zu entwickeln. Solche Algorithmen sollten einerseits Visibility Culling1, Level-of-Detail, (LOD), Out-of-Core Speicherverwaltung und Kompression unterstützen. Anderseits sollte diese Optimierung sehr effizient arbeiten, um das Rendering nicht noch zusätzlich zu behindern. Dies erfordert die Entwicklung paralleler Verfahren, die in der Lage sind, die enorme Datenflut effizient zu verarbeiten. Der Kernbeitrag dieser Arbeit sind neuartige Algorithmen und Datenstrukturen, die speziell für eine effiziente parallele Datenverarbeitung entwickelt wurden und in der Lage sind sehr komplexe Modelle und Szenen in Echtzeit darzustellen, sowie zu modellieren. Diese Algorithmen arbeiten in zwei Phasen: Zunächst wird in einer Offline-Phase die Datenstruktur erzeugt und für parallele Verarbeitung optimiert. Die optimierte Datenstruktur wird dann in der zweiten Phase für das Echtzeitrendering verwendet. Ein weiterer Beitrag dieser Arbeit ist ein Algorithmus, welcher in der Lage ist, einen sehr realistisch wirkenden Planeten prozedural zu generieren und in Echtzeit zu rendern

Graph Spectral Image Processing

Recent advent of graph signal processing (GSP) has spurred intensive studies of signals that live naturally on irregular data kernels described by graphs (e.g., social networks, wireless sensor networks). Though a digital image contains pixels that reside on a regularly sampled 2D grid, if one can design an appropriate underlying graph connecting pixels with weights that reflect the image structure, then one can interpret the image (or image patch) as a signal on a graph, and apply GSP tools for processing and analysis of the signal in graph spectral domain. In this article, we overview recent graph spectral techniques in GSP specifically for image / video processing. The topics covered include image compression, image restoration, image filtering and image segmentation

Multiresolution Techniques for Real–Time Visualization of Urban Environments and Terrains

In recent times we are witnessing a steep increase in the availability of data coming from real–life environments. Nowadays, virtually everyone connected to the Internet may have instant access to a tremendous amount of data coming from satellite elevation maps, airborne time-of-flight scanners and digital cameras, street–level photographs and even cadastral maps. As for other, more traditional types of media such as pictures and videos, users of digital exploration softwares expect commodity hardware to exhibit good performance for interactive purposes, regardless of the dataset size. In this thesis we propose novel solutions to the problem of rendering large terrain and urban models on commodity platforms, both for local and remote exploration. Our solutions build on the concept of multiresolution representation, where alternative representations of the same data with different accuracy are used to selectively distribute the computational power, and consequently the visual accuracy, where it is more needed on the base of the user’s point of view. In particular, we will introduce an efficient multiresolution data compression technique for planar and spherical surfaces applied to terrain datasets which is able to handle huge amount of information at a planetary scale. We will also describe a novel data structure for compact storage and rendering of urban entities such as buildings to allow real–time exploration of cityscapes from a remote online repository. Moreover, we will show how recent technologies can be exploited to transparently integrate virtual exploration and general computer graphics techniques with web applications

Modelado jerárquico de objetos 3D con superficies de subdivisión

Las SSs (Superficies de Subdivisión) son un potente paradigma de modelado de objetos 3D (tridimensionales) que establece un puente entre los dos enfoques tradicionales a la aproximación de superficies, basados en mallas poligonales y de parches alabeados, que conllevan problemas uno y otro. Los esquemas de subdivisión permiten definir una superficie suave (a tramos), como las más frecuentes en la práctica, como el límite de un proceso recursivo de refinamiento de una malla de control burda, que puede ser descrita muy compactamente. Además, la recursividad inherente a las SSs establece naturalmente una relación de anidamiento piramidal entre las mallas / NDs (Niveles de Detalle) generadas/os sucesivamente, por lo que las SSs se prestan extraordinariamente al AMRO (Análisis Multiresolución mediante Ondículas) de superficies, que tiene aplicaciones prácticas inmediatas e interesantísimas, como la codificación y la edición jerárquicas de modelos 3D. Empezamos describiendo los vínculos entre las tres áreas que han servido de base a nuestro trabajo (SSs, extracción automática de NDs y AMRO) para explicar como encajan estas tres piezas del puzzle del modelado jerárquico de objetos de 3D con SSs. El AMRO consiste en descomponer una función en una versión burda suya y un conjunto de refinamientos aditivos anidados jerárquicamente llamados "coeficientes ondiculares". La teoría clásica de ondículas estudia las señales clásicas nD: las definidas sobre dominios paramétricos homeomorfos a R" o (0,1)n como el audio (n=1), las imágenes (n=2) o el vídeo (n=3). En topologías menos triviales, como las variedades 2D) (superficies en el espacio 3D), el AMRO no es tan obvio, pero sigue siendo posible si se enfoca desde la perspectiva de las SSs. Basta con partir de una malla burda que aproxime a un bajo ND la superficie considerada, subdividirla recursivamente y, al hacerlo, ir añadiendo los coeficientes ondiculares, que son los detalles 3D necesarios para obtener aproximaciones más y más finas a la superficie original. Pasamos después a las aplicaciones prácticas que constituyen nuestros principal desarrollo original y, en particular, presentamos una técnica de codificación jerárquica de modelos 3D basada en SSs, que actúa sobre los detalles 3D mencionados: los expresa en un referencial normal loscal; los organiza según una estructura jerárquica basada en facetas; los cuantifica dedicando menos bits a sus componentes tangenciales, menos energéticas, y los "escalariza"; y los codifica dinalmente gracias a una técnica similar al SPIHT (Set Partitioning In Hierarchical Tress) de Said y Pearlman. El resultado es un código completamente embebido y al menos dos veces más compacto, para superficies mayormente suaves, que los obtenidos con técnicas de codificación progresiva de mallas 3D publicadas previamente, en las que además los NDs no están anidados piramidalmente. Finalmente, describimos varios métodos auxiliares que hemos desarrollado, mejorando técnicas previas y creando otras propias, ya que una solución completa al modelado de objetos 3D con SSs requiere resolver otros dos problemas. El primero es la extracción de una malla base (triangular, en nuestro caso) de la superficie original, habitualmente dada por una malla triangular fina con conectividad arbitraria. El segundo es la generación de un remallado recursivo con conectividad de subdivisión de la malla original/objetivo mediante un refinamiento recursivo de la malla base, calculando así los detalles 3D necesarios para corregir las posiciones predichas por la subdivisión para nuevos vértices

Non-linear subdivision of univariate signals and discrete surfaces

During the last 20 years, the joint expansion of computing power, computer graphics, networking capabilities and multiresolution analysis have stimulated several research domains, and developed the need for new types of data such as 3D models, i.e. discrete surfaces. In the intersection between multiresolution analysis and computer graphics, subdivision methods, i.e. iterative refinement procedures of curves or surfaces, have a non-negligible place, since they are a basic component needed to adapt existing multiresolution techniques dedicated to signals and images to more complicated data such as discrete surfaces represented by polygonal meshes. Such representations are of great interest since they make polygonal meshes nearly as exible as higher level 3D model representations, such as piecewise polynomial based surfaces (e.g. NURBS, B-splines...). The generalization of subdivision methods from univariate data to polygonal meshes is relatively simple in case of a regular mesh but becomes less straightforward when handling irregularities. Moreover, in the linear univariate case, obtaining a smoother limit curve is achieved by increasing the size of the support of the subdivision scheme, which is not a trivial operation in the case of a surface subdivision scheme without a priori assumptions on the mesh. While many linear subdivision methods are available, the studies concerning more general non-linear methods are relatively sparse, whereas such techniques could be used to achieve better results without increasing the size support. The goal of this study is to propose and to analyze a binary non-linear interpolatory subdivision method. The proposed technique uses local polar coordinates to compute the positions of the newly inserted points. It is shown that the method converges toward continuous limit functions. The proposed univariate scheme is extended to triangular meshes, possibly with boundaries. In order to evaluate characteristics of the proposed scheme which are not proved analytically, numerical estimates to study convergence, regularity of the limit function and approximation order are studied and validated using known linear schemes of identical support. The convergence criterion is adapted to surface subdivision via a Hausdorff distance-based metric. The evolution of Gaussian and mean curvature of limit surfaces is also studied and compared against theoretical values when available. An application of surface subdivision to build a multiresolution representation of 3D models is also studied. In particular, the efficiency of such a representation for compression and in terms of rate-distortion of such a representation is shown. An alternate to the initial SPIHT-based encoding, based on the JPEG 2000 image compression standard method. This method makes possible partial decoding of the compressed model in both SNR-progressive and level-progressive ways, while adding only a minimal overhead when compared to SPIHT