What's the Situation with Intelligent Mesh Generation: A Survey and Perspectives

Intelligent Mesh Generation (IMG) represents a novel and promising field of research, utilizing machine learning techniques to generate meshes. Despite its relative infancy, IMG has significantly broadened the adaptability and practicality of mesh generation techniques, delivering numerous breakthroughs and unveiling potential future pathways. However, a noticeable void exists in the contemporary literature concerning comprehensive surveys of IMG methods. This paper endeavors to fill this gap by providing a systematic and thorough survey of the current IMG landscape. With a focus on 113 preliminary IMG methods, we undertake a meticulous analysis from various angles, encompassing core algorithm techniques and their application scope, agent learning objectives, data types, targeted challenges, as well as advantages and limitations. We have curated and categorized the literature, proposing three unique taxonomies based on key techniques, output mesh unit elements, and relevant input data types. This paper also underscores several promising future research directions and challenges in IMG. To augment reader accessibility, a dedicated IMG project page is available at \url{https://github.com/xzb030/IMG_Survey}

An Efficient Volumetric Framework for Shape Tracking

International audienceRecovering 3D shape motion using visual information is an important problem with many applications in computer vision and computer graphics, among other domains. Most existing approaches rely on surface-based strategies, where surface models are fit to visual surface observations. While numerically plausible, this paradigm ignores the fact that the observed surfaces often delimit volumetric shapes, for which deformations are constrained by the volume inside the shape. Consequently, surface-based strategies can fail when the observations define several feasible surfaces, whereas volumetric considerations are more restrictive with respect to the admissible solutions. In this work, we investigate a novel volumetric shape parametrization to track shapes over temporal sequences. In constrast to Eulerian grid discretizations of the observation space, such as voxels, we consider general shape tesselations yielding more convenient cell decompositions, in particular the Centroidal Voronoi Tesselation. With this shape representation, we devise a tracking method that exploits volumetric information, both for the data term evaluating observation conformity, and for expressing deformation constraints that enforce prior assumptions on motion. Experiments on several datasets demonstrate similar or improved precisions over state-of-the-art methods, as well as improved robustness, a critical issue when tracking sequentially over time frames

Computerized Analysis of Magnetic Resonance Images to Study Cerebral Anatomy in Developing Neonates

The study of cerebral anatomy in developing neonates is of great importance for the understanding of brain development during the early period of life. This dissertation therefore focuses on three challenges in the modelling of cerebral anatomy in neonates during brain development. The methods that have been developed all use Magnetic Resonance Images (MRI) as source data. To facilitate study of vascular development in the neonatal period, a set of image analysis algorithms are developed to automatically extract and model cerebral vessel trees. The whole process consists of cerebral vessel tracking from automatically placed seed points, vessel tree generation, and vasculature registration and matching. These algorithms have been tested on clinical Time-of- Flight (TOF) MR angiographic datasets. To facilitate study of the neonatal cortex a complete cerebral cortex segmentation and reconstruction pipeline has been developed. Segmentation of the neonatal cortex is not effectively done by existing algorithms designed for the adult brain because the contrast between grey and white matter is reversed. This causes pixels containing tissue mixtures to be incorrectly labelled by conventional methods. The neonatal cortical segmentation method that has been developed is based on a novel expectation-maximization (EM) method with explicit correction for mislabelled partial volume voxels. Based on the resulting cortical segmentation, an implicit surface evolution technique is adopted for the reconstruction of the cortex in neonates. The performance of the method is investigated by performing a detailed landmark study. To facilitate study of cortical development, a cortical surface registration algorithm for aligning the cortical surface is developed. The method first inflates extracted cortical surfaces and then performs a non-rigid surface registration using free-form deformations (FFDs) to remove residual alignment. Validation experiments using data labelled by an expert observer demonstrate that the method can capture local changes and follow the growth of specific sulcus

Improving automatic rigging for 3D humanoid characters

In the field of computer animation the process of creating an animated character is usually a long and tedious task. An animation character is usually efined by a 3D mesh (a set of triangles in the space) that gives its external appearance or shape to the character. It also used to have an inner structure, the skeleton. When a skeleton is associated to a character mesh, this association is called skeleton binding, and a skeleton bound to a character mesh is an animation rig. Rigging from scratch a character can be a very boring process. The definition and creation of a centered skeleton together with the ’painting’, by an artist,of the influence parameters between the skeleton and the mesh (the skinning) s the most demanding part to achieve an acceptable behavior for a character. This rigging process can be simplified and accelerated using an automatic rigging method. Automatic rigging methods consist in taking as input a 3D mesh, generate a skeleton based in the shape of the original model, bound the input mesh to the generated skeleton, and finally to compute a set of parameters based in a chosen skinning method. The main objective of this thesis is to generate a method for rigging a 3D arbitrary model with minimum user interaction. This can be useful to people without experience in the animation field or to experienced people to accelerate the rigging process from days to hours or minutes depending the needed quality. Having in mind this situation we have designed our method as a set of tools that can be applied to general input models defined by an artist. The contributions made in the development of this thesis can be summarized as: • Generation of an animation Rig: Having an arbitrary closed mesh we have implemented a thinning method to create first an unrefined geometry skeleton that captures the topology and pose of the input character. Using this geometric skeleton as starting point we use a refining method that creates an adjusted logic skeleton based in a template, or may be defined by the user, that is compatible with the current animation formats. The output logic skeleton is specific for each character, and it is bounded to the input mesh to create an animation rig. • Skinning: Having defined an animation rig for an arbitrary mesh we have developed an improved skinning method; this method is based on the Linear Blend Skinning(LBS) algorithm. Our contributions in the skinning field can be sub-divided in: – We propose a segmentation method that works as the core element in a weight assigning algorithm and a skinning lgorithm, we also have developed an automatic algorithm to compute the skin weights of the LBS Skinning of a rigged polygonal mesh. – Our proposed skinning algorithm uses as base the features of the LBS Skinning. The main purpose of the developed algorithm is to solve the well-known ”candy wrap” artifact; that produces a substantial loss of volume when a link of an animation skeleton is rotated over its own axis. We have compared our results with the most important methods in the skinning field, such as Dual Quaternion Skinning (DQS) and LBS, achieving a better performance over DQS and an improvement in quality over LBS. • Animation tools: We have developed a set of Autodesk Maya commands that works together as rig tool, using our previous proposed methods. • Animation loader: Moreover, an animation loader tool has been implemented, that allows the user to load animations from a skeleton with different structure to a rigged 3D model. The contributions previously described has been published in 3 research papers, the first two were presented in international congresses and the third one was acepted for its publication in an JCR indexed journal.En el campo de la animación por computadora el proceso de crear un personaje de animación es comúnmente una tarea larga y tediosa. Un personaje de animación está definido usualmente por una malla tridimensional (un conjunto de triángulos en el espacio) que le dan su apariencia externa y forma al personaje. Es igualmente común que este tenga una estructura interna, un esqueleto de animación. Cuando un esqueleto esta asociado con una malla tridimensional, a esta asociación se le llama ligado de esqueleto, y un esqueleto ligado a la mallade un personaje es conocido en inglés como "animation rig" (el conjunto de elementos necesarios, que unidos sirven para animar un personaje). Hacer el rigging desde cero de un personaje puede ser un proceso muy tedioso. La definición y creación de un esqueleto centrado en la malla junto con el "pintado" por medio de un artista de los parámetros de influencia entre el esqueleto y la malla 3D (lo que se conoce como skinning) es la parte mas demandante para alcanzar un compartimiento aceptable al deformase (moverse) la malla de un personaje. Los métodos de rigging automáticos consisten en tomar una malla tridimensional como elemento de entrada, generar un esqueleto basado en la forma del modelo original, ligar la malla de entrada al esqueleto generado y finamente calcular el conjunto de parámetros utilizados por el método de skinning elegido. El principal objetivo de esta tesis es el generar un método de rigging para un modelo tridimensional arbitrario con una interacción mínima del usuario. Este método puede ser útil para gente con poca experiencia en el campo de la animación, o para gente experimentada que quiera acelerar el proceso de rigging de días a horas o inclusive minutos, dependiendo de la calidad requerida. Teniendo en mente esta situación, hemos diseñado nuestro método como un conjunto de herramientas las cuales pueden ser aplicadas a modelos de entrada generados por cualquier artista. Las contribuciones hechas en el desarrollo de esta tesis pueden resumirse a: -Generación de un rig de animación: Teniendo una malla cerrada cualquiera, hemos implementado un método para crear primero un esqueleto geométrico sin refinar, el cual capture la pose y la topología del personaje usado como elemento de entrada. Tomando este esqueleto geométrico como punto de partida usamos un método de refinado que crea un "esqueleto lógico" adaptado a la forma del geométrico basándonos en una plantilla definida por el usuario o previamente definida, que sea compatible con los formatos actuales de animación. El esqueleto lógico generado será especifico para cada personaje, y esta ligado a la malla de entrada para así crear un rig de animación. - Skinning: Teniendo definido un rig de animación para una malla de entrada arbitraria, hemos desarrollado un método mejorado de skinning, este método sera basado en el algoritmo "Linear Blending Skinnig" (algoritmo de skinning por combinación lineal, LBS por sus siglas en inglés). Nuestras contribuciones en el campo del skinnig son: - Proponemos un nuevo método de segmentación de mallas que sea la parte medular para algoritmos de asignación automática de pesos y de skinning, también hemos desarrollado un algoritmo automático que calcule los pesos utilizados por el algoritmo LBS para una malla poligonal que tenga un rig de animación. - Nuestro algoritmo de skinning propuesto usará como base las características del algoritmo LBS. El principal propósito del algoritmo desarrollado es el solucionar el defecto conocido como "envoltura de caramelo" (candy wrapper artifact), que produce una substancial perdida de volumen al rotar una de las articulaciones del esqueleto de animación sobre su propio eje. Nuestros resultados son comparados con los métodos mas importantes en el campo del skinning tal como Cuaterniones Duales (Dual Quaternions Skinning, DQS) y LBS, alcanzando un mejor desempeño que DQS y una mejora importante sobre LBSPostprint (published version

Template based shape processing

As computers can only represent and process discrete data, information gathered from the real world always has to be sampled. While it is nowadays possible to sample many signals accurately and thus generate high-quality reconstructions (for example of images and audio data), accurately and densely sampling 3D geometry is still a challenge. The signal samples may be corrupted by noise and outliers, and contain large holes due to occlusions. These issues become even more pronounced when also considering the temporal domain. Because of this, developing methods for accurate reconstruction of shapes from a sparse set of discrete data is an important aspect of the computer graphics processing pipeline. In this thesis we propose novel approaches to including semantic knowledge into reconstruction processes using template based shape processing. We formulate shape reconstruction as a deformable template fitting process, where we try to fit a given template model to the sampled data. This approach allows us to present novel solutions to several fundamental problems in the area of shape reconstruction. We address static problems like constrained texture mapping and semantically meaningful hole-filling in surface reconstruction from 3D scans, temporal problems such as mesh based performance capture, and finally dynamic problems like the estimation of physically based material parameters of animated templates.Analoge Signale müssen digitalisiert werden um sie auf modernen Computern speichern und verarbeiten zu können. Für viele Signale, wie zum Beispiel Bilder oder Tondaten, existieren heutzutage effektive und effiziente Digitalisierungstechniken. Aus den so gewonnenen Daten können die ursprünglichen Signale hinreichend akkurat wiederhergestellt werden. Im Gegensatz dazu stellt das präzise und effiziente Digitalisieren und Rekonstruieren von 3D- oder gar 4D-Geometrie immer noch eine Herausforderung dar. So führen Verdeckungen und Fehler während der Digitalisierung zu Löchern und verrauschten Meßdaten. Die Erforschung von akkuraten Rekonstruktionsmethoden für diese groben digitalen Daten ist daher ein entscheidender Schritt in der Entwicklung moderner Verarbeitungsmethoden in der Computergrafik. In dieser Dissertation wird veranschaulicht, wie deformierbare geometrische Modelle als Vorlage genutzt werden können, um semantische Informationen in die robuste Rekonstruktion von 3D- und 4D Geometrie einfließen zu lassen. Dadurch wird es möglich, neue Lösungsansätze für mehrere grundlegenden Probleme der Computergrafik zu entwickeln. So können mit dieser Technik Löcher in digitalisierten 3D Modellen semantisch sinnvoll aufgefüllt, oder detailgetreue virtuelle Kopien von Darstellern und ihrer dynamischen Kleidung zu erzeugt werden

Power Diagrams and Sparse Paged Grids for High Resolution Adaptive Liquids

© ACM, 2017. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Aanjaneya, M., Gao, M., Liu, H., Batty, C., & Sifakis, E. (2017). Power Diagrams and Sparse Paged Grids for High Resolution Adaptive Liquids. ACM Trans. Graph., 36(4), 140:1–140:12. https://doi.org/10.1145/3072959.3073625We present an efficient and scalable octree-inspired fluid simulation framework with the flexibility to leverage adaptivity in any part of the computational domain, even when resolution transitions reach the free surface. Our methodology ensures symmetry, definiteness and second order accuracy of the discrete Poisson operator, and eliminates numerical and visual artifacts of prior octree schemes. This is achieved by adapting the operators acting on the octree's simulation variables to reflect the structure and connectivity of a power diagram, which recovers primal-dual mesh orthogonality and eliminates problematic T-junction configurations. We show how such operators can be efficiently implemented using a pyramid of sparsely populated uniform grids, enhancing the regularity of operations and facilitating parallelization. A novel scheme is proposed for encoding the topology of the power diagram in the neighborhood of each octree cell, allowing us to locally reconstruct it on the fly via a lookup table, rather than resorting to costly explicit meshing. The pressure Poisson equation is solved via a highly efficient, matrix-free multigrid preconditioner for Conjugate Gradient, adapted to the power diagram discretization. We use another sparsely populated uniform grid for high resolution interface tracking with a narrow band level set representation. Using the recently introduced SPGrid data structure, sparse uniform grids in both the power diagram discretization and our narrow band level set can be compactly stored and efficiently updated via streaming operations. Additionally, we present enhancements to adaptive level set advection, velocity extrapolation, and the fast marching method for redistancing. Our overall framework gracefully accommodates the task of dynamically adapting the octree topology during simulation. We demonstrate end-to-end simulations of complex adaptive flows in irregularly shaped domains, with tens of millions of degrees of freedom.National Science FoundationNational Sciences and Engineering Research Council of Canad