Probabilistic Roadmaps for Virtual Camera Pathing with Cinematographic Principles

As technology use increases in the world and inundates everyday life, the visual aspect of technology or computer graphics becomes increasingly important. This thesis presents a system for the automatic generation of virtual camera paths for fly-throughs of a digital scene. The sample scene used in this work is an underwater setting featuring a shipwreck model with other virtual underwater elements such as rocks, bubbles and caustics. The digital shipwreck model was reconstructed from an actual World War II shipwreck, resting off the coast of Malta. Video and sonar scans from an autonomous underwater vehicle were used in a photogrammetry pipeline to create the model. This thesis presents an algorithm to automatically generate virtual camera paths using a robotics motion planning algorithm, specifically the probabilistic roadmap. This algorithm uses a rapidly-exploring random tree to quickly cover a space and generate small maps with good coverage. For this work, the camera pitch and height along a specified path were automatically generated using cinematographic and geometric principles. These principles were used to evaluate potential viewpoints and influence whether or not a view is used in the final path. A computational evaluation of ‘the rule of thirds’ and evaluation of the model normals relative to the camera viewpoint are used to represent cinematography and geometry principles. In addition to the system that automatically generates virtual camera paths, a user study is presented which evaluates ten different videos produced via camera paths with this system. The videos were created using different viewpoint evaluation methods and different path generation characteristics. The user study indicates that users prefer paths generated by our system over flat and randomly generated paths. Specifically, users prefer paths generated using the computational evaluation of the rule of thirds and paths that show the wreck from a large variety of angles but without too much camera undulation

Surface collision detection for virtual prototyping

This paper presents an efficient collision detection algorithm designed to support assembly and maintenance simulation of complex assemblies. This approach exploits the surface knowledge, available from CAD models, to determine intersecting surfaces. It proposes a novel combination of Overlapping Axis-Aligned Bounding Box (OAABB) and R-tree structures to gain considerable performance improvements. This paper also shows an efficient traversal algorithm based on the R-tree structure of Axis-Aligned Bounding Boxes to determine intersecting objects and intersecting surfaces between three-dimensional components, for supporting the recognition of constraints in assembly and disassembly operations in virtual prototyping environments. The implementation of the proposed collision detection algorithm performs well against moderately complex industrial case studies. Current experimental results show that this implementation is effective in determining intersecting surfaces at interactive rates with moderately complex real case studies.info:eu-repo/semantics/publishedVersio

The Software Required for the Computer Generation of Virtual Environments

Presence, Vol. 2, No. 2, pp. 130-140..Accepted/Published Paper (Refereed

Continuous collision detection for ellipsoids

We present an accurate and efficient algorithm for continuous collision detection between two moving ellipsoids. We start with a highly optimized implementation of interference testing between two stationary ellipsoids based on an algebraic condition described in terms of the signs of roots of the characteristic equation of two ellipsoids. Then we derive a time-dependent characteristic equation for two moving ellipsoids, which enables us to develop a real-time algorithm for computing the time intervals in which two moving ellipsoids collide. The effectiveness of our approach is demonstrated with several practical examples. © 2006 IEEE.published_or_final_versio

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

The International Grid (iGrid): Empowering Global Research Community Networking Using High Performance International Internet Services

The Electronic Visualization Laboratory (EVL) at the University of Illinois at Chicago and Indiana University collaborated on a major research demonstration at the IEEE/ACM Supercomputing '98 (SC'98) conference in Orlando, Florida, November 7-13, 1998, to showcase the evolution and importance of global research community networking. Collaborators worked together to solve complex computational problems using advanced high-speed networks to access geographically-distributed computing, storage, and display resources. It is the collection of computing and communication resources that we refer to as the International Grid (iGrid). This paper presents an overview of the grid testbed, some of the underlying technologies used to enable distributed computing and collaborative problem solving, and descriptions of the applications. It concludes with recommendations for the future of global research community networking, based on the experiences of iGrid participants from the USA, Australia, Canada, Germany, Japan, The Netherlands, Russia, Switzerland, Singapore, and Taiwan

Fast swept-volume distance for robust collision detection

The need for collision detection arises in several robotics areas, including motion-planning, online collision avoidance, and simulation. At the heart of most current methods are algorithms for interference detection and/or distance computation. A few recent algorithms and implementations are very fast, but to use them for accurate collision detection, very small step sizes can be necessary, reducing their effective efficiency. We present a fast, implemented technique for doing exact distance computation and interference detection for translationally-swept bodies. For rotationally swept bodies, we adapt this technique to improve accuracy, for any given step size, in distance computation and interference detection. We present preliminary experiments that show that the combination of basic and swept-body calculations holds much promise for faster accurate collision detection

Neural radiance fields in the industrial and robotics domain: applications, research opportunities and use cases

The proliferation of technologies, such as extended reality (XR), has increased the demand for high-quality three-dimensional (3D) graphical representations. Industrial 3D applications encompass computer-aided design (CAD), finite element analysis (FEA), scanning, and robotics. However, current methods employed for industrial 3D representations suffer from high implementation costs and reliance on manual human input for accurate 3D modeling. To address these challenges, neural radiance fields (NeRFs) have emerged as a promising approach for learning 3D scene representations based on provided training 2D images. Despite a growing interest in NeRFs, their potential applications in various industrial subdomains are still unexplored. In this paper, we deliver a comprehensive examination of NeRF industrial applications while also providing direction for future research endeavors. We also present a series of proof-of-concept experiments that demonstrate the potential of NeRFs in the industrial domain. These experiments include NeRF-based video compression techniques and using NeRFs for 3D motion estimation in the context of collision avoidance. In the video compression experiment, our results show compression savings up to 48\% and 74\% for resolutions of 1920x1080 and 300x168, respectively. The motion estimation experiment used a 3D animation of a robotic arm to train Dynamic-NeRF (D-NeRF) and achieved an average peak signal-to-noise ratio (PSNR) of disparity map with the value of 23 dB and an structural similarity index measure (SSIM) 0.97