Liquid simulation with mesh-based surface tracking

Animating detailed liquid surfaces has always been a challenge for computer graphics researchers and visual effects artists. Over the past few years, researchers in this field have focused on mesh-based surface tracking to synthesize extremely detailed liquid surfaces as efficiently as possible. This course provides a solid understanding of the steps required to create a fluid simulator with a mesh-based liquid surface. The course begins with an overview of several existing liquid-surface-tracking techniques and the pros and cons of each method. Then it explains how to embed a triangle mesh into a finite-difference-based fluid simulator and describes several methods for allowing the liquid surface to merge together or break apart. The final section showcases the benefits and further applications of a mesh-based liquid surface, highlighting state-of-the-art methods for tracking colors and textures, maintaining liquid volume, preserving small surface features, and simulating realistic surface-tension waves

GPU-Based Optimization of a Free-Viewpoint Video System

We present a method for optimizing the reconstruction and rendering of 3D objects from multiple images by utilizing the latest features of consumer-level graphics hardware based on shader model 4.0. We accelerate visual hull reconstruction by rewriting a shape-from-silhouette algorithm to execute on the GPU's parallel architecture. Rendering a is optimized through the application of geometry shaders to generate billboarding microfacets textured with captured images. We also present a method for handling occlusion in the camera selection process that is optimized for execution on the GPU. Execution time is further improved by rendering intermediate results directly to texture to minimize the number of data transfers between graphics and main memory. We show our GPU based system to be significantly more efficient than a purely CPU-based approach, due to the parallel nature of the GPU, while maintaining graphical quality

Animating physical phenomena with embedded surface meshes

Accurate computational representations of highly deformable surfaces are indispensable in the fields of computer animation, medical simulation, computer vision, digital modeling, and computational physics. The focus of this dissertation is on the animation of physics-based phenomena with highly detailed deformable surfaces represented by triangle meshes. We first present results from an algorithm that generates continuum mechanics animations with intricate surface features. This method combines a finite element method with a tetrahedral mesh generator and a high resolution surface mesh, and it is orders of magnitude more efficient than previous approaches. Next, we present an efficient solution for the challenging problem of computing topological changes in detailed dynamic surface meshes. We then introduce a new physics-inspired surface tracking algorithm that is capable of preserving arbitrarily thin features and reproducing realistic fine-scale topological changes like Rayleigh-Plateau instabilities. This physics-inspired surface tracking technique also opens the door for a unique coupling between surficial finite element methods and volumetric finite difference methods, in order to simulate liquid surface tension phenomena more efficiently than any previous method. Due to its dramatic increase in computational resolution and efficiency, this method yielded the first computer simulations of a fully developed crown splash with droplet pinch off.Ph.D.Committee Chair: Turk, Greg; Committee Member: Essa, Irfan; Committee Member: Liu, Karen; Committee Member: Mucha, Peter J.; Committee Member: Rossignac, Jare

GPU Optimization of an Existing Free-Viewpoint Video System

Many video reconstruction systems seek to recreate a scene from captured video sequences but are unable to perform at interactive framerates. This project presents the optimization of such a system by utilizing a Graphics Processing Unit (GPU). The specialized nature of the GPU offers many challenges in non-traditional graphics pipelines, but can offer great performance benefits. This paper presents the process by which a next-generation GPU is utilized to accelerate the visual hull reconstruction and rendering in Cinematized Reality

Robust surface modelling of visual hull from multiple silhouettes

Reconstructing depth information from images is one of the actively researched themes in computer vision and its application involves most vision research areas from object recognition to realistic visualisation. Amongst other useful vision-based reconstruction techniques, this thesis extensively investigates the visual hull (VH) concept for volume approximation and its robust surface modelling when various views of an object are available. Assuming that multiple images are captured from a circular motion, projection matrices are generally parameterised in terms of a rotation angle from a reference position in order to facilitate the multi-camera calibration. However, this assumption is often violated in practice, i.e., a pure rotation in a planar motion with accurate rotation angle is hardly realisable. To address this problem, at first, this thesis proposes a calibration method associated with the approximate circular motion. With these modified projection matrices, a resulting VH is represented by a hierarchical tree structure of voxels from which surfaces are extracted by the Marching cubes (MC) algorithm. However, the surfaces may have unexpected artefacts caused by a coarser volume reconstruction, the topological ambiguity of the MC algorithm, and imperfect image processing or calibration result. To avoid this sensitivity, this thesis proposes a robust surface construction algorithm which initially classifies local convex regions from imperfect MC vertices and then aggregates local surfaces constructed by the 3D convex hull algorithm. Furthermore, this thesis also explores the use of wide baseline images to refine a coarse VH using an affine invariant region descriptor. This improves the quality of VH when a small number of initial views is given. In conclusion, the proposed methods achieve a 3D model with enhanced accuracy. Also, robust surface modelling is retained when silhouette images are degraded by practical noise

From small to large baseline multiview stereo : dealing with blur, clutter and occlusions

This thesis addresses the problem of reconstructing the three-dimensional (3D) digital model of a scene from a collection of two-dimensional (2D) images taken from it. To address this fundamental computer vision problem, we propose three algorithms. They are the main contributions of this thesis. First, we solve multiview stereo with the o -axis aperture camera. This system has a very small baseline as images are captured from viewpoints close to each other. The key idea is to change the size or the 3D location of the aperture of the camera so as to extract selected portions of the scene. Our imaging model takes both defocus and stereo information into account and allows to solve shape reconstruction and image restoration in one go. The o -axis aperture camera can be used in a small-scale space where the camera motion is constrained by the surrounding environment, such as in 3D endoscopy. Second, to solve multiview stereo with large baseline, we present a framework that poses the problem of recovering a 3D surface in the scene as a regularized minimal partition problem of a visibility function. The formulation is convex and hence guarantees that the solution converges to the global minimum. Our formulation is robust to view-varying extensive occlusions, clutter and image noise. At any stage during the estimation process the method does not rely on the visual hull, 2D silhouettes, approximate depth maps, or knowing which views are dependent(i.e., overlapping) and which are independent( i.e., non overlapping). Furthermore, the degenerate solution, the null surface, is not included as a global solution in this formulation. One limitation of this algorithm is that its computation complexity grows with the number of views that we combine simultaneously. To address this limitation, we propose a third formulation. In this formulation, the visibility functions are integrated within a narrow band around the estimated surface by setting weights to each point along optical rays. This thesis presents technical descriptions for each algorithm and detailed analyses to show how these algorithms improve existing reconstruction techniques

Tangible Scalar Fields

Data Visualization is a field that explores how to most efficiently convey information to the user, most often via visual representations like plots, graphs or glyphs. While this field of research has had great growth within the last couple of years, most of the work has been focused on the visual part of the human visual and auditory system - much less visualization work has been done in regards to the visually impaired. In this thesis, we will look at some previous methods and techniques for visualizing scalar fields via the sense of touch, and additionally provide two novel approaches to visualize a two-dimensional scalar field. Our first approach creates passive physicalizations from a scalar field in a semi-automatic pipeline by encoding the scalar value and field coordinates as positions in 3D space, which we use to construct a triangular mesh built from hexagonal pillars that can be printed on a 3D printer. We further enhance our mesh by encoding a directional attribute on the pillars, creating a visual encoding of the model orientation and improving upon a readability issue by mirroring the mesh. Our second approach uses a haptic force-feedback device to simulate the feeling of moving across a surface based on the scalar field by replicating three physical forces: the normal force, the friction force and the gravity force. We also further extend our approach by introducing a local encoding of global information about the scalar field via a volume representation build from the scalar field.Masteroppgave i informatikkINF399MAMN-PROGMAMN-IN