Real-time deformable objects in collaborative virtual environments

This thesis presents a method for deformations on closed surfaces in 3D over a network, which is suitable for simulation of tissue and organs for training purposes, as well as cloth simulation in collaborative virtual environments (CVE). CVE's are extensively used for training, design and gaming for several years. To demonstrate a deformable object on a CVE, we employ a real-time physical simulation of a uniformtension- membrane, based on linear finite-element-discretization of the surface yielding a sparse linear system of equations, which is solved using the Runge-Kutta Fehlberg method. The proposed method introduces an architecture that distributes the computational load of physical simulation between clients. As our approach requires a uniform-mesh representation of the simulated structure, we also designed and implemented an algorithm that converts irregularly triangulated genus zero surfaces into a uniform triangular mesh with regular connectivity. This algorithm uses springembedders for stretch optimization of the spherical parameterization step. The strength of our approach comes from the subdivision methodology that enables to use multi-resolution surfaces for graphical representation, physical simulation, and network transmission, without compromising simulation accuracy and visual quality

Entropy guided visualization and analysis of multivariate spatio-temporal data generated by physically based simulation

Flow fields produced by physically based simulations are subsets of multivariate spatiotemporal data, and have been in interest of many researchers for visualization, since the data complexity makes it difficult to extract representative views for the interpretation of fluid behavior. In this thesis, we utilize Information Theory to find entropy maps for vector flow fields, and use entropy maps to aid visualization and analysis of the flow fields. Our major contribution is to use Principal Component Analyses (PCA) to find a projection that has the maximal directional variation in polar coordinates for each sampling window in order to generate histograms according to the projected 3D vector field, producing results with fewer artifacts than the traditional methods. Entropy guided visualization of different data sets are presented to evaluate proposed method for the generation of entropy maps. High entropy regions and coherent directional components of the flow fields are visible without cluttering to reveal fluid behavior in rendered images. In addition to using data sets those are available for research purposes, we have developed a fluid simulation framework using Smoothed Particle Hydrodynamics (SPH) to produce flow fields. SPH is a widely used method for fluid simulations, and used to generate data sets that are difficult to interpret with direct visualization techniques. A moderate improvement for the performance and stability of SPH implementations is also proposed with the use of fractional derivatives, which are known to be useful for approximating particle behavior immersed in fluids

DockPro: A VR-Based Tool for Protein-Protein Docking Problem

Proteins are large molecules that are vital for all living organisms and they are essential components of many industrial products. The process of binding a protein to another is called protein-protein docking. Many automated algorithms have been proposed to find docking configurations that might yield promising protein-protein complexes. However, these automated methods are likely to come up with false positives and have high computational costs. Consequently, Virtual Reality has been used to take advantage of user's experience on the problem; and proposed applications can be further improved. Haptic devices have been used for molecular docking problems; but they are inappropriate for protein-protein docking due to their workspace limitations. Instead of haptic rendering of forces, we provide a novel visual feedback for simulating physicochemical forces of proteins. We propose an interactive 3D application, DockPro, which enables domain experts to come up with dockings of protein-protein couples by using magnetic trackers and gloves in front of a large display

Real-time simulation of autonomous vehicles on planet-sized continuous LOD terrains

Real-Time visualization of interactive simulation environments using large datasets of height fields became feasible using current off the shelf graphics hardware. Our approach provides continuous level of detail rendering of high detailed, planet sized terrains using restricted quad-trees without re-sampling data points. The presented method preserves the original planet coordinate frame of the data gathered from the Mars Orbiter Laser Altimeter with 128 samples/degree resolution for vehicle simulation purposes. Furthermore the algorithm avoids discontinuities at the block boundaries occurring at latitudes

DockPro: A VR-Based Tool for Protein-Protein Docking Problem

International audienceProteins are large molecules that are vital for all living organisms and they are essential components of many industrial products. The process of binding a protein to another is called protein-protein docking. Many automated algorithms have been proposed to find docking configurations that might yield promising protein-protein complexes. However, these automated methods are likely to come up with false positives and have high computational costs. Consequently, Virtual Reality has been used to take advantage of user’s experience on the problem; and proposed applications can be further improved. Haptic devices have been used for molecular docking problems; but they are inappropriate for protein-protein docking due to their workspace limitations. Instead of haptic rendering of forces, we provide a novel visual feedback for simulating physicochemical forces of proteins. We propose an interactive 3D application, DockPro, which enables domain experts to come up with dockings of protein-protein couples by using magnetic trackers and gloves in front of a large display

Dynamic visualization of geographic networks using surface deformations with constraints

This paper addresses the problem of displaying large network data within geographic context in a 3D interactive environment. Networks often have a spatial component, and maintaining the geographic context of the network data in visualization is imperative for understanding related human behavior and enabling a semantic interpretation. We propose a novel visualization system, where spatial network data is visualized as deformations on a 3D map. The developed system enables users gleaning dominant tendencies for each node without examining each relation separately. Conventional node and link displays are incorporated for detailed examination of a portion of data on demand. Having two modalities for displaying data as a whole and a detailed portion of it, our visualization system provides a reading for the data at micro and macro levels