Chad Mourning

An overview of the STEAMiE Educational game Engine

Today, there exists a significant disparity in the degree of technological development between commercial and educational games. The STEAMiE educational engine is a cutting-edge system used to create advanced, realistic, immersive learning environments. These environments have been shown to influence comprehension and retention of hard-to-teach science concepts. This paper will present an overview of the features of our STEAMiE educational engine and how to use it to create games/simulations capable of enhancing a userpsilas learning experience. The STEAMiE educational engine contains a rich feature set allowing for development of powerful modules within a short period of time. From a development point of view, the STEAMiE educational enginepsilas object oriented design is modular and can be easily extended to support new functionality in a timely manner. This significantly shortens development time and abstracts complexities from the developer allowing for clean and efficient implementations of games and simulations.

Interactive mesostructures

This paper presents a technique for interactively deforming and colliding with mesostructures at a per-texel level. It is compatible with a broad range of existing mesostructure rendering techniques including both safe and unsafe ray-height field intersection algorithms. This technique integrates well with existing physics engines and is able to reduce traditional 3D geometrical deformations (vertex-based) to 2D image space operations (pixel-based) that are parallelized on a GPU without CPU-GPU data shuffling. Additionally, surface and material properties may be specified at a per-texel level enabling a mesostructure to possess varying attributes intrinsic to its surface and collision behavior; furthermore, this offers an image-based alternative to traditional decals. This technique provides a simple way to make almost every surface in a virtual world responsive to user actions and events. It requires no preprocessing time and storage requirements of one additional texture or less. The algorithm uses existing displacement map algorithms as well as existing physics engines and can be easily incorporated into new or existing game pipelines.

GPU acceleration of robust point matching

Robust Point Matching (RPM) is a common image registration algorithm, yet its large computational complexity prohibits registering large point sets in a timely manner. With recent advances in General Purpose Graphical Processing Units (GPGPUs), commodity hardware is capable of greatly reducing the execution time of RPM when non-rigidly aligning thousands of data points. In this paper, we identify areas where parallelism can be exploited in the RPM algorithm, and investigate a GPU-based approach to accelerate the implementation. Other common RPM implementations are compared with our solution. Experiments on synthetic and real data sets show that our approach achieves close to linear speed-up with respect to total computational power over the widely used Matlab implementation. Our tests indicate that utilizing our implementation on current state of the art GPU technology would enable the use of vastly greater point set sizes.

An analysis of impostor based level of detail approximations for LIDAR data

LIDAR (Light Detection and Ranging) [1] is a remote sensing technology that is growing in popularity in varied and diverse disciplines. Modern LIDAR systems can produce substantial amounts of data in very brief amounts of time, so one of the greatest challenges facing researchers is processing and visualizing all of this information, particularly in real time. Ideally, a scientific visualization of a set of LIDAR data should provide an accurate view of all the available information; however, sometimes it is beneficial to exchange a small portion of that accuracy for the increased usability and flexibility of a real-time interactive display. The goal of this research is to characterize under what conditions the level-of-detail rendering technique known as impostors [2-4] can effectively optimize the inherent trade-offs between accuracy and interactivity in large-scale point cloud datasets.

A flight tested wake turbulence aware altimeter

A flying aircraft disturbs the local atmosphere through which it flies creating a turbulent vortex at each wing tip known as a wake vortex. These vortices can persist for several minutes and endanger other aircraft traversing that turbulent airspace; large vortices are essentially invisible horizontal tornadoes and are a grave threat to smaller aircraft, especially during landing and take off. Accidents related to wake turbulence have resulted in both loss of life and aircraft destruction in the United States and around the world. Currently no cockpit instrumentation exists that tracks wake vortices and enables a pilot to sense and avoid wake turbulence in real-time. This paper presents a prototype of a novel, flight tested instrument that tracks wake vortices and presents this information to a pilot in real time using a synthetic virtual world augmented with wake turbulence information.

An investigation of TREPAN utilising a continuous oracle model

TREPAN is decision tree algorithm that utilises artificial neural networks (ANNs) in order to improve partitioning conditions when sample data is sparse. When sample sizes are limited during the tree-induction process, TREPAN relies on an ANN oracle in order to create artificial sample instances. The original TREPAN implementation was limited to ANNs that were designed to be classification models. In other words, TREPAN was incapable of building decision trees from ANN models that were continuous in nature. Thus, the objective of this research was to modify the original implementation of TREPAN in order to develop and test decision trees derived from continuous-based ANN models. Though the modification were minor, they are significant because it provides researchers and practitioners an additional strategy to extract knowledge from a trained ANN regardless of its design. This research also explores how TEPAN|s adjustable settings influence predictive performances based on a dataset|s complexity and size.

Disocclusion Mitigation for Image Based Point Cloud Imposters

Image based imposters suffer from common errors called disocclusion artifacts where portions of the scene that should be occluded by real geometry are visible when using image based imposters. These artifacts are the result of parallax error created by camera motion where regions of a mesh that were not visible at the time of imposter generation have become visible. This paper presents a computationally inexpensive on-line technique to resolve these disocclusions by stretching existing imposter texture information over new geometry bridging the gap between imposters. This paper also includes an analysis of six automatic metrics for similarity between output frames of a flight path using this novel technique and the impersonated data, to quantify the quality of the technique compared to the original scene and other level-of-detail techniques.

Interactive Mesostructures withVolumetric Collisions

This paper presents a technique for interactively colliding with and deforming mesostructures at a per-texel level. It is compatible with a broad range of existing mesostructure rendering techniques including both safe and unsafe ray-height field intersection algorithms. This technique is able to replace traditional 3D geometrical deformations (vertex-based) with 2D image space operations (pixel-based) that are parallelized on a GPU without CPU-GPU data shuffling and integrates well with existing physics engines. Additionally, surface and material properties may be specified at a per-texel level enabling a mesostructure to possess varying attributes intrinsic to its surface and collision behavior. Furthermore, this approach may replace traditional decals with image-based operations that naturally accumulate deformations without inserting any new geometry. This technique provides a simple and efficient way to make almost every surface in a virtual world responsive to user actions and events. It requires no preprocessing time and storage requirements of one additional texture or less. The algorithm uses existing inverse displacement map algorithms as well as existing physics engines and can be easily incorporated into new or existing game pipelines.

Comparison of aircraft state prediction methods under sensor uncertainty

The paper discusses a comparison of various aircraft state prediction methods in the presence of sensor uncertainty. Aircraft state prediction and, specifically, energy state prediction is an important step in providing the flight crew with visual and aural cues to improve their airplane state awareness (ASA) and, thus, increase aviation safety as the lack of aircraft state awareness has been one of the leading causal and contributing factors in aviation accidents. This paper focusses on predictive alerting methods to predict (a) stall and overspeed conditions, (b) high-and-fast conditions, and (c) automation mode transitions. The proposed method estimates and subsequently predicts the aircraft state based on (i) aircraft state related information output by the onboard avionics, (ii) the configuration of the aircraft, (iii) appropriate aircraft dynamics models of both the active modes and the modes to which can be transitioned via simple pilot actions, and (iv) accurate models of the uncertainty of the dynamics and sensors. To compare the performance of the various methods, this paper analyzed flight data collected during a recent NASA flight simulator study in which eleven commercial airline crews (22 pilots) completed more than 230 flights.

Disocclusion mitigation for point cloud imposters

Image based imposters suffer from common errors called disocclusion artifacts where portions of the scene that should be occluded by real geometry are visible when using image based imposters. These artifacts are the result of parallax error created by camera motion where regions of a mesh that were not visible at the time of imposter generation have become visible. This document presents an analysis of a computationally inexpensive on-line technique [Mourning et al. 2014] to resolve these disocclusions by stretching existing imposter [Maciel and Shirley 1995] texture information over new geometry bridging the gap between imposters. [Mourning et al. 2014] only presented automatic metrics showing improved image quality compared to traditional techniques; in order to corroborate the findings in [Mourning et al. 2014], human trials were performed to determine if human subjects found a similar increase in image quality. Results show a statistically significant improvement in image quality over traditional imposters.