Audio-Material Reconstruction for Virtualized Reality Using a Probabilistic Damping Model.

Modal sound synthesis has been used to create realistic sounds from rigid-body objects, but requires accurate real-world material parameters. These material parameters can be estimated from recorded sounds of an impacted object, but external factors can interfere with accurate parameter estimation. We present a novel technique for estimating the damping parameters of materials from recorded impact sounds that probabilistically models these external factors. We represent the combined effects of material damping, support damping, and sampling inaccuracies with a probabilistic generative model, then use maximum likelihood estimation to fit a damping model to recorded data. This technique greatly reduces the human effort needed and does not require the precise object geometry or the exact hit location. We validate the effectiveness of this technique with a comprehensive analysis of a synthetic dataset and a perceptual study on object identification. We also present a study establishing human performance on the same parameter estimation task for comparison.

Pairwise Force SPH Model for Real-Time Multi-Interaction Applications.

In this paper, we present a novel pairwise-force smoothed particle hydrodynamics (PF-SPH) model to enable simulation of various interactions at interfaces in real time. Realistic capture of interactions at interfaces is a challenging problem for SPH-based simulations, especially for scenarios involving multiple interactions at different interfaces. Our PF-SPH model can readily handle multiple types of interactions simultaneously in a single simulation; its basis is to use a larger support radius than that used in standard SPH. We adopt a novel anisotropic filtering term to further improve the performance of interaction forces. The proposed model is stable; furthermore, it avoids the particle clustering problem which commonly occurs at the free surface. We show how our model can be used to capture various interactions. We also consider the close connection between droplets and bubbles, and show how to animate bubbles rising in liquid as well as bubbles in air. Our method is versatile, physically plausible and easy-to-implement. Examples are provided to demonstrate the capabilities and effectiveness of our approach.

MaterialCloning: Acquiring Elasticity Parameters from Images for Medical Applications.

We present a practical approach for automatically estimating the material properties of soft bodies from two sets of images, taken before and after deformation. We reconstruct 3D geometry from the given sets of multiple-view images; we use a coupled simulation-optimization-identification framework to deform one soft body at its original, non-deformed state to match the deformed geometry of the same object in its deformed state. For shape correspondence, we use a distance-based error metric to compare the estimated deformation fields against the actual deformation field from the reconstructed geometry. The optimal set of material parameters is thereby determined by minimizing the error metric function. This method can simultaneously recover the elasticity parameters of multiple types of soft bodies using Finite Element Method-based simulation (of either linear or nonlinear materials undergoing large deformation) and particle-swarm optimization methods. We demonstrate this approach on real-time interaction with virtual organs in patient-specific surgical simulation, using parameters acquired from low-resolution medical images. We also highlight the results on physics-based animation of virtual objects using sketches from an artist's conception.

Identifying Opportunities for Virtual Reality Simulation in Surgical Education: A Review of the Proceedings from the Innovation, Design, and Emerging Alliances in Surgery (IDEAS) Conference: VR Surgery.

OBJECTIVES: To conduct a review of the state of virtual reality (VR) simulation technology, to identify areas of surgical education that have the greatest potential to benefit from it, and to identify challenges to implementation. BACKGROUND DATA: Simulation is an increasingly important part of surgical training. VR is a developing platform for using simulation to teach technical skills, behavioral skills, and entire procedures to trainees and practicing surgeons worldwide. Questions exist regarding the science behind the technology and most effective usage of VR simulation. A symposium was held to address these issues. METHODS: Engineers, educators, and surgeons held a conference in November 2013 both to review the background science behind simulation technology and to create guidelines for its use in teaching and credentialing trainees and surgeons in practice. RESULTS: Several technologic challenges were identified that must be overcome in order for VR simulation to be useful in surgery. Specific areas of student, resident, and practicing surgeon training and testing that would likely benefit from VR were identified: technical skills, team training and decision-making skills, and patient safety, such as in use of electrosurgical equipment. CONCLUSIONS: VR simulation has the potential to become an essential piece of surgical education curriculum but depends heavily on the establishment of an agreed upon set of goals. Researchers and clinicians must collaborate to allocate funding toward projects that help achieve these goals. The recommendations outlined here should guide further study and implementation of VR simulation.

Continuum modeling of crowd turbulence.

With the growth in world population, the density of crowds in public places has been increasing steadily, leading to a higher incidence of crowd disasters at high densities. Recent research suggests that emergent chaotic behavior at high densities-known collectively as crowd turbulence-is to blame. Thus, a deeper understanding of crowd turbulence is needed to facilitate efforts to prevent and plan for chaotic conditions in high-density crowds. However, it has been noted that existing algorithms modeling collision avoidance cannot faithfully simulate crowd turbulence. We hypothesize that simulation of crowd turbulence requires modeling of both collision avoidance and frictional forces arising from pedestrian interactions. Accordingly, we propose a model for turbulent crowd simulation, which incorporates a model for interpersonal stress and acceleration constraints similar to real-world pedestrians. Our simulated results demonstrate a close correspondence with observed metrics for crowd turbulence as measured in known crowd disasters.

Hybrid Long-Range Collision Avoidance for Crowd Simulation.

Local collision avoidance algorithms in crowd simulation often ignore agents beyond a neighborhood of a certain size. This cutoff can result in sharp changes in trajectory when large groups of agents enter or exit these neighborhoods. In this work, we exploit the insight that exact collision avoidance is not necessary between agents at such large distances, and propose a novel algorithm for extending existing collision avoidance algorithms to perform approximate, long-range collision avoidance. Our formulation performs long-range collision avoidance for distant agent groups to efficiently compute trajectories that are smoother than those obtained with state-of-the-art techniques and at faster rates. Comparison to real-world data demonstrates that crowds simulated with our algorithm exhibit an improved speed sensitivity to density similar to human crowds. Another issue often sidestepped in existing work is that discrete and continuum collision avoidance algorithms have different regions of applicability. For example, low-density crowds cannot be modeled as a continuum, while high-density crowds can be expensive to model using discrete methods. We formulate a hybrid technique for crowd simulation which can accurately and efficiently simulate crowds at any density with seamless transitions between continuum and discrete representations. Our approach blends results from continuum and discrete algorithms, based on local density and velocity variance. In addition to being robust across a variety of group scenarios, it is also highly efficient, running at interactive rates for thousands of agents on portable systems.

Flow field modulation.

The nonlinear and nonstationary nature of Navier-Stokes equations produces fluid flows that can be noticeably different in appearance with subtle changes. In this paper, we introduce a method that can analyze the intrinsic multiscale features of flow fields from a decomposition point of view, by using the Hilbert-Huang transform method on 3D fluid simulation. We show how this method can provide insights to flow styles and help modulate the fluid simulation with its internal physical information. We provide easy-to-implement algorithms that can be integrated with standard grid-based fluid simulation methods and demonstrate how this approach can modulate the flow field and guide the simulation with different flow styles. The modulation is straightforward and relates directly to the flow's visual effect, with moderate computational overhead.

Auditory perception of geometry-invariant material properties.

Accurately modeling the intrinsic material-dependent damping property for interactive sound rendering is a challenging problem. The Rayleigh damping model is commonly regarded as an adequate engineering model for interactive sound synthesis in virtual environment applications, but this assumption has never been rigorously analyzed. In this paper, we conduct a formal evaluation of this model. Our goal is to determine if auditory perception of material under Rayleigh damping assumption is 'geometry-invariant', i.e. if this approximation model is transferable across different shapes and sizes. First, audio recordings of same-material objects in various shapes and sizes are analyzed to determine if they can be approximated by the Rayleigh damping model with a single set of parameters. Next, we design and conduct a series of psychoacoustic experiments, in subjects evaluate if audio clips synthesized using the Rayleigh damping model are from the same material, when we alter the material, shape, and size parameters. Through both quantitative and qualitative evaluation, we show that the acoustic properties of the Rayleigh damping model for a single material is generally preserved across different geometries of objects consisting of homogeneous materials and is therefore a suitable, geometry-invariant sound model. Our study results also show that consistent with prior crossmodal expectations, visual perception of geometry can affect the auditory perception of materials. These findings facilitate the wide adoption of Rayleigh damping for interactive auditory systems and enable reuse of material parameters under this approximation model across different shapes and sizes, without laborious per-object parameter tuning.

Least-effort trajectories lead to emergent crowd behaviors.

Pedestrian crowds often have been modeled as many-particle systems, usually using computer models known as multiagent simulations. The key challenge in modeling crowds is to develop rules that guide how the particles or agents interact with each other in a way that faithfully reproduces paths and behaviors commonly seen in real human crowds. Here, we propose a simple and intuitive formulation of these rules based on biomechanical measurements and the principle of least effort. We present a constrained optimization method to compute collision-free paths of minimum caloric energy for each agent, from which collective crowd behaviors can be reproduced. We show that our method reproduces common crowd phenomena, such as arching and self-organization into lanes. We also validate the flow rates and paths produced by our method and compare them to those of real-world crowd trajectories.

Transforming GIS data into functional road models for large-scale traffic simulation.

There exists a vast amount of geographic information system (GIS) data that model road networks around the world as polylines with attributes. In this form, the data are insufficient for applications such as simulation and 3D visualization-tools which will grow in power and demand as sensor data become more pervasive and as governments try to optimize their existing physical infrastructure. In this paper, we propose an efficient method for enhancing a road map from a GIS database to create a geometrically and topologically consistent 3D model to be used in real-time traffic simulation, interactive visualization of virtual worlds, and autonomous vehicle navigation. The resulting representation provides important road features for traffic simulations, including ramps, highways, overpasses, legal merge zones, and intersections with arbitrary states, and it is independent of the simulation methodologies. We test the 3D models of road networks generated by our algorithm on real-time traffic simulation using both macroscopic and microscopic techniques.

Directing crowd simulations using navigation fields.

We present a novel approach to direct and control virtual crowds using navigation fields. Our method guides one or more agents toward desired goals based on guidance fields. The system allows the user to specify these fields by either sketching paths directly in the scene via an intuitive authoring interface or by importing motion flow fields extracted from crowd video footage. We propose a novel formulation to blend input guidance fields to create singularity-free, goal-directed navigation fields. Our method can be easily combined with the most current local collision avoidance methods and we use two such methods as examples to highlight the potential of our approach. We illustrate its performance on several simulation scenarios.

Virtualized Traffic: reconstructing traffic flows from discrete spatiotemporal data.

We present a novel concept, Virtualized Traffic, to reconstruct and visualize continuous traffic flows from discrete spatiotemporal data provided by traffic sensors or generated artificially to enhance a sense of immersion in a dynamic virtual world. Given the positions of each car at two recorded locations on a highway and the corresponding time instances, our approach can reconstruct the traffic flows (i.e., the dynamic motions of multiple cars over time) between the two locations along the highway for immersive visualization of virtual cities or other environments. Our algorithm is applicable to high-density traffic on highways with an arbitrary number of lanes and takes into account the geometric, kinematic, and dynamic constraints on the cars. Our method reconstructs the car motion that automatically minimizes the number of lane changes, respects safety distance to other cars, and computes the acceleration necessary to obtain a smooth traffic flow subject to the given constraints. Furthermore, our framework can process a continuous stream of input data in real time, enabling the users to view virtualized traffic events in a virtual world as they occur. We demonstrate our reconstruction technique with both synthetic and real-world input.

Efficient and accurate sound propagation using adaptive rectangular decomposition.

Accurate sound rendering can add significant realism to complement visual display in interactive applications, as well as facilitate acoustic predictions for many engineering applications, like accurate acoustic analysis for architectural design. Numerical simulation can provide this realism most naturally by modeling the underlying physics of wave propagation. However, wave simulation has traditionally posed a tough computational challenge. In this paper, we present a technique which relies on an adaptive rectangular decomposition of 3D scenes to enable efficient and accurate simulation of sound propagation in complex virtual environments. It exploits the known analytical solution of the Wave Equation in rectangular domains, and utilizes an efficient implementation of the Discrete Cosine Transform on Graphics Processors (GPU) to achieve at least a 100-fold performance gain compared to a standard Finite-Difference Time-Domain (FDTD) implementation with comparable accuracy, while also being 10-fold more memory efficient. Consequently, we are able to perform accurate numerical acoustic simulation on large, complex scenes in the kilohertz range. To the best of our knowledge, it was not previously possible to perform such simulations on a desktop computer. Our work thus enables acoustic analysis on large scenes and auditory display for complex virtual environments on commodity hardware.

Interactive navigation of heterogeneous agents using adaptive roadmaps.

We present a novel algorithm for collision-free navigation of a large number of independent agents in complex and dynamic environments. We introduce adaptive roadmaps to perform global path planning for each agent simultaneously. Our algorithm takes into account dynamic obstacles and interagents interaction forces to continuously update the roadmap based on a physically-based dynamics simulator. In order to efficiently update the links, we perform adaptive particle-based sampling along the links. We also introduce the notion of 'link bands' to resolve collisions among multiple agents. In practice, our algorithm can perform real-time navigation of hundreds and thousands of human agents in indoor and outdoor scenes.

Physically-based validation of deformable medical image registration.

We propose a new approach for validating deformable image registration algorithms. Since difference images do not necessarily reflect the 3D correspondence of organs, we propose to use the deformation fields generated in our FEM-based simulations to assess the displacement resulted from other registration methods. Unlike traditional FEM-based registration methods, the boundary condition for the target organ is not given explicitly. Instead it is driven by inter-organ contact forces generated by boundary conditions on surrounding organs to reduce the uncertainty induced by geometry-based surface matching. To validate our system, real CT images of the male pelvis are analyzed, and the prostate can be reasonably registered without matching its surface to the image. Several registration methods are then evaluated using our system.

Virtual reality software and technology.

This special issue contains an introductory survey on 3D user interfaces by leading VR authorities and significantly expanded versions of the four best short papers from the proceedings of the 14th ACM Symposium on Virtual Reality Software and Technology (VRST 07).