Attack on the clones: managing player perceptions of visual variety and believability in video game crowds

Crowds of non-player characters are increasingly common in contemporary video games. It is often the case that individual models are re-used, lowering visual variety in the crowd and potentially affecting realism and believability. This paper explores a number of approaches to increase visual diversity in large game crowds, and discusses a procedural solution for generating diverse non-player character models. This is evaluated using mixed methods, including a “clone spotting” activity and measurement of impact on computational overheads, in order to present a multi-faceted and adjustable solution to increase believability and variety in video game crowds

Using Simulation and Domain Adaptation to Improve Efficiency of Deep Robotic Grasping

Instrumenting and collecting annotated visual grasping datasets to train modern machine learning algorithms can be extremely time-consuming and expensive. An appealing alternative is to use off-the-shelf simulators to render synthetic data for which ground-truth annotations are generated automatically. Unfortunately, models trained purely on simulated data often fail to generalize to the real world. We study how randomized simulated environments and domain adaptation methods can be extended to train a grasping system to grasp novel objects from raw monocular RGB images. We extensively evaluate our approaches with a total of more than 25,000 physical test grasps, studying a range of simulation conditions and domain adaptation methods, including a novel extension of pixel-level domain adaptation that we term the GraspGAN. We show that, by using synthetic data and domain adaptation, we are able to reduce the number of real-world samples needed to achieve a given level of performance by up to 50 times, using only randomly generated simulated objects. We also show that by using only unlabeled real-world data and our GraspGAN methodology, we obtain real-world grasping performance without any real-world labels that is similar to that achieved with 939,777 labeled real-world samples.Comment: 9 pages, 5 figures, 3 table

Real Time Animation of Virtual Humans: A Trade-off Between Naturalness and Control

Virtual humans are employed in many interactive applications using 3D virtual environments, including (serious) games. The motion of such virtual humans should look realistic (or ‘natural’) and allow interaction with the surroundings and other (virtual) humans. Current animation techniques differ in the trade-off they offer between motion naturalness and the control that can be exerted over the motion. We show mechanisms to parametrize, combine (on different body parts) and concatenate motions generated by different animation techniques. We discuss several aspects of motion naturalness and show how it can be evaluated. We conclude by showing the promise of combinations of different animation paradigms to enhance both naturalness and control

Procedural Modeling and Physically Based Rendering for Synthetic Data Generation in Automotive Applications

We present an overview and evaluation of a new, systematic approach for generation of highly realistic, annotated synthetic data for training of deep neural networks in computer vision tasks. The main contribution is a procedural world modeling approach enabling high variability coupled with physically accurate image synthesis, and is a departure from the hand-modeled virtual worlds and approximate image synthesis methods used in real-time applications. The benefits of our approach include flexible, physically accurate and scalable image synthesis, implicit wide coverage of classes and features, and complete data introspection for annotations, which all contribute to quality and cost efficiency. To evaluate our approach and the efficacy of the resulting data, we use semantic segmentation for autonomous vehicles and robotic navigation as the main application, and we train multiple deep learning architectures using synthetic data with and without fine tuning on organic (i.e. real-world) data. The evaluation shows that our approach improves the neural network's performance and that even modest implementation efforts produce state-of-the-art results.Comment: The project web page at http://vcl.itn.liu.se/publications/2017/TKWU17/ contains a version of the paper with high-resolution images as well as additional materia

Virtual reality as an educational tool in interior architecture

Ankara : The Department of Interior Architecture and Environmental Design and the Institute of Fine Arts of Bilkent Univ., 1997.Thesis (Master's) -- Bilkent University, 1997.Includes bibliographical references.This thesis discusses the use of virtual reality technology as an educational tool in interior architectural design. As a result of this discussion, it is proposed that virtual reality can be of use in aiding three-dimensional design and visualization, and may speed up the design process. It may also be of help in getting the designers/students more involved in their design projects. Virtual reality can enhance the capacity of designers to design in three dimensions. The virtual reality environment used in designing should be capable of aiding both the design and the presentation process. The tradeoffs of the technology, newly emerging trends and future directions in virtual reality are discussed.Aktaş, OrkunM.S

Virtual tour

Interactive 3D Visualization of Architectural models might be the best way to get some idea about an Architecture Plan. Photo-realistic visualization often attracts the investors and customers for whom the architectural blueprints are obscure. Architectural Visualization is considered to have a bright future ahead of it as more and more architects and real estate developers are using this technology. Virtual Walk-through can give not only ideas about your building but its interiors and design too. The Architectural Virtual Environment also most widely used in Gaming and Entertainment Industry in creating a complex movie scenes or a game environment

Gravitational Lensing by Spinning Black Holes in Astrophysics, and in the Movie Interstellar

Interstellar is the first Hollywood movie to attempt depicting a black hole as it would actually be seen by somebody nearby. For this we developed a code called DNGR (Double Negative Gravitational Renderer) to solve the equations for ray-bundle (light-beam) propagation through the curved spacetime of a spinning (Kerr) black hole, and to render IMAX-quality, rapidly changing images. Our ray-bundle techniques were crucial for achieving IMAX-quality smoothness without flickering. This paper has four purposes: (i) To describe DNGR for physicists and CGI practitioners . (ii) To present the equations we use, when the camera is in arbitrary motion at an arbitrary location near a Kerr black hole, for mapping light sources to camera images via elliptical ray bundles. (iii) To describe new insights, from DNGR, into gravitational lensing when the camera is near the spinning black hole, rather than far away as in almost all prior studies. (iv) To describe how the images of the black hole Gargantua and its accretion disk, in the movie \emph{Interstellar}, were generated with DNGR. There are no new astrophysical insights in this accretion-disk section of the paper, but disk novices may find it pedagogically interesting, and movie buffs may find its discussions of Interstellar interesting.Comment: 46 pages, 17 figure