Image Display and Manipulation System (IDAMS) program documentation, Appendixes A-D

The IDAMS Processor is a package of task routines and support software that performs convolution filtering, image expansion, fast Fourier transformation, and other operations on a digital image tape. A unique task control card for that program, together with any necessary parameter cards, selects each processing technique to be applied to the input image. A variable number of tasks can be selected for execution by including the proper task and parameter cards in the input deck. An executive maintains control of the run; it initiates execution of each task in turn and handles any necessary error processing

Engineering data compendium. Human perception and performance, volume 3

The concept underlying the Engineering Data Compendium was the product of a research and development program (Integrated Perceptual Information for Designers project) aimed at facilitating the application of basic research findings in human performance to the design of military crew systems. The principal objective was to develop a workable strategy for: (1) identifying and distilling information of potential value to system design from existing research literature, and (2) presenting this technical information in a way that would aid its accessibility, interpretability, and applicability by system designers. The present four volumes of the Engineering Data Compendium represent the first implementation of this strategy. This is Volume 3, containing sections on Human Language Processing, Operator Motion Control, Effects of Environmental Stressors, Display Interfaces, and Control Interfaces (Real/Virtual)

Analyse und Modellierung dynamischer dreidimensionaler Szenen unter Verwendung einer Laufzeitkamera

Many applications in Computer Vision require the automatic analysis and reconstruction of static and dynamic scenes. Therefore the automatic analysis of three-dimensional scenes is an area which is intensively investigated. Most approaches focus on the reconstruction of rigid geometry because the reconstruction of non-rigid geometry is far more challenging and requires that three-dimensional data is available at high frame-rates. Rigid scene analysis is for example used in autonomous navigation, for surveillance and for the conservation of cultural heritage. The analysis and reconstruction of non-rigid geometry on the other hand provides a lot more possibilities, not only for the above-mentioned applications. In the production of media content for television or cinema the analysis, recording and playback of full 3D content can be used to generate new views of real scenes or to replace real actors by animated artificial characters. The most important requirement for the analysis of dynamic content is the availability of reliable three-dimensional scene data. Mostly stereo methods have been used to compute the depth of scene points, but these methods are computationally expensive and do not provide sufficient quality in real-time. In recent years the so-called Time-of-Flight cameras have left the prototype stadium and are now capable to deliver dense depth information in real-time at reasonable quality and price. This thesis investigates the suitability of these cameras for the purpose of dynamic three-dimensional scene analysis. Before a Time-of-Flight camera can be used to analyze three-dimensional scenes it has to be calibrated internally and externally. Moreover, Time-of-Flight cameras suffer from systematic depth measurement errors due to their operation principle. This thesis proposes an approach to estimate all necessary parameters in one calibration step. In the following the reconstruction of rigid environments and objects is investigated and solutions for these tasks are presented. The reconstruction of dynamic scenes and the generation of novel views of dynamic scenes is achieved by the introduction of a volumetric data structure to store and fuse the depth measurements and their change over time. Finally a Mixed Reality system is presented in which the contributions of this thesis are brought together. This system is able to combine real and artificial scene elements with correct mutual occlusion, mutual shadowing and physical interaction. This thesis shows that Time-of-Flight cameras are a suitable choice for the analysis of rigid as well as non-rigid scenes under certain conditions. It contains important contributions for the necessary steps of calibration, preprocessing of depth data and reconstruction and analysis of three-dimensional scenes.Viele Anwendungen des Maschinellen Sehens benötigen die automatische Analyse und Rekonstruktion von statischen und dynamischen Szenen. Deshalb ist die automatische Analyse von dreidimensionalen Szenen und Objekten ein Bereich der intensiv erforscht wird. Die meisten Ansätze konzentrieren sich auf die Rekonstruktion statischer Szenen, da die Rekonstruktion nicht-statischer Geometrien viel herausfordernder ist und voraussetzt, dass dreidimensionale Szeneninformation mit hoher zeitlicher Auflösung verfügbar ist. Statische Szenenanalyse wird beispielsweise in der autonomen Navigation, für die Überwachung und für die Erhaltung des Kulturerbes eingesetzt. Andererseits eröffnet die Analyse und Rekonstruktion nicht-statischer Geometrie viel mehr Möglichkeiten, nicht nur für die bereits erwähnten Anwendungen. In der Produktion von Medieninhalten für Film und Fernsehen kann die Analyse und die Aufnahme und Wiedergabe von vollständig dreidimensionalen Inhalten verwendet werden um neue Ansichten realer Szenen zu erzeugen oder echte Schauspieler durch animierte virtuelle Charaktere zu ersetzen. Die wichtigste Voraussetzung für die Analyse von dynamischen Inhalten ist die Verfügbarkeit von zuverlässigen dreidimensionalen Szeneninformationen. Um die Entfernung von Punkten in der Szene zu bestimmen wurden meistens Stereo-Verfahren eingesetzt, aber diese Verfahren benötigen viel Rechenzeit und erreichen in Echtzeit nicht die benötigte Qualität. In den letzten Jahren haben die so genannten Laufzeitkameras das Stadium der Prototypen verlassen und sind jetzt in der Lage dichte Tiefeninformationen in vernünftiger Qualität zu einem vernünftigen Preis zu liefern. Diese Arbeit untersucht die Eignung dieser Kameras für die Analyse nicht-statischer dreidimensionaler Szenen. Bevor eine Laufzeitkamera für die Analyse eingesetzt werden kann muss sie intern und extern kalibriert werden. Darüber hinaus leiden Laufzeitkameras an systematischen Fehlern bei der Entfernungsmessung, bedingt durch ihr Funktionsprinzip. Diese Arbeit stellt ein Verfahren vor um alle nötigen Parameter in einem Kalibrierschritt zu berechnen. Im Weiteren wird die Rekonstruktion von statischen Umgebungen und Objekten untersucht und Lösungen für diese Aufgaben werden präsentiert. Die Rekonstruktion von nicht-statischen Szenen und die Erzeugung neuer Ansichten solcher Szenen wird mit der Einführung einer volumetrischen Datenstruktur erreicht, in der die Tiefenmessungen und ihr Änderungen über die Zeit gespeichert und fusioniert werden. Schließlich wird ein Mixed Reality System vorgestellt in welchem die Beiträge dieser Arbeit zusammengeführt werden. Dieses System ist in der Lage reale und künstliche Szenenelemente unter Beachtung von korrekter gegenseitiger Verdeckung, Schattenwurf und physikalischer Interaktion zu kombinieren. Diese Arbeit zeigt, dass Laufzeitkameras unter bestimmten Voraussetzungen eine geeignete Wahl für die Analyse von statischen und nicht-statischen Szenen sind. Sie enthält wichtige Beiträge für die notwendigen Schritte der Kalibrierung, der Vorverarbeitung von Tiefendaten und der Rekonstruktion und der Analyse von dreidimensionalen Szenen

Engineering data compendium. Human perception and performance. User's guide

The concept underlying the Engineering Data Compendium was the product of a research and development program (Integrated Perceptual Information for Designers project) aimed at facilitating the application of basic research findings in human performance to the design and military crew systems. The principal objective was to develop a workable strategy for: (1) identifying and distilling information of potential value to system design from the existing research literature, and (2) presenting this technical information in a way that would aid its accessibility, interpretability, and applicability by systems designers. The present four volumes of the Engineering Data Compendium represent the first implementation of this strategy. This is the first volume, the User's Guide, containing a description of the program and instructions for its use

Optical Communication

Optical communication is very much useful in telecommunication systems, data processing and networking. It consists of a transmitter that encodes a message into an optical signal, a channel that carries the signal to its desired destination, and a receiver that reproduces the message from the received optical signal. It presents up to date results on communication systems, along with the explanations of their relevance, from leading researchers in this field. The chapters cover general concepts of optical communication, components, systems, networks, signal processing and MIMO systems. In recent years, optical components and other enhanced signal processing functions are also considered in depth for optical communications systems. The researcher has also concentrated on optical devices, networking, signal processing, and MIMO systems and other enhanced functions for optical communication. This book is targeted at research, development and design engineers from the teams in manufacturing industry, academia and telecommunication industries

The social poetics of analog virtual worlds : toying with alternate realities

textWhile online virtual worlds draw increasingly wider audiences of players and scholars alike, offline games continue to evolve into more complex and socially layered forms as well. This dissertation argues that virtual worlds need not exist as online, digital environments alone and probes three genres of non-digital gaming for evidence of the virtual: tabletop role-playing games, murder-mystery events, and localized alternate reality games. More broadly, then, this dissertation is about deliberate make-belief: practiced by adults, taken seriously by participants, engaged with for long hours at a time, performed in public, and integrated into everyday social relationships. Drawing on scholars who study games as social activities (McGonigal 2006, Montola 2012) and social institutions (Goffman 1974, Searle 1995), I present three ethnographic case studies that illustrate how complex forms of social gaming can conjure and sustain environments best understood as analog virtual worlds. Through the widespread use of mobile technologies and the concerted efforts of innovators, game spaces are increasingly permeating our everyday lives on- and offline. This dissolving boundary demands anthropologists to revisit questions of how, where, and with whom we play games. Dovetailing Martin Heidegger’s notions of worlding and poiesis to the semiotics of C.S. Peirce, this dissertation investigates how new forms of social gaming demonstrate the same qualities of shared intentionality, intersubjectivity, and performance essential to the production of new social meaning and cultural forms. Following, I situate the bold ethnographic case studies of make-belief in dialogue with scholars who figure exclusively online virtual worlds (Castronova 2005, Taylor 2006, Boellstorff 2008) and argue that analyzing both on- and offline virtual worlds together can help scholars better understand the fundamental nature of social interaction and shared intentionality, those everyday mechanisms that both sustain personal relationships on the one hand and maintain our broadest and most serious social institutions on the other.Anthropolog

Characteristics of flight simulator visual systems

The physical parameters of the flight simulator visual system that characterize the system and determine its fidelity are identified and defined. The characteristics of visual simulation systems are discussed in terms of the basic categories of spatial, energy, and temporal properties corresponding to the three fundamental quantities of length, mass, and time. Each of these parameters are further addressed in relation to its effect, its appropriate units or descriptors, methods of measurement, and its use or importance to image quality

Identification of Technologies for Provision of Future Aeronautical Communications

This report describes the process, findings, and recommendations of the second of three phases of the Future Communications Study (FCS) technology investigation conducted by NASA Glenn Research Center and ITT Advanced Engineering & Sciences Division for the Federal Aviation Administration (FAA). The FCS is a collaborative research effort between the FAA and Eurocontrol to address frequency congestion and spectrum depletion for safety critical airground communications. The goal of the technology investigation is to identify technologies that can support the longterm aeronautical mobile communication operating concept. A derived set of evaluation criteria traceable to the operating concept document is presented. An adaptation of the analytical hierarchy process is described and recommended for selecting candidates for detailed evaluation. Evaluations of a subset of technologies brought forward from the prescreening process are provided. Five of those are identified as candidates with the highest potential for continental airspace solutions in L-band (P-34, W-CDMA, LDL, B-VHF, and E-TDMA). Additional technologies are identified as best performers in the unique environments of remote/oceanic airspace in the satellite bands (Inmarsat SBB and a custom satellite solution) and the airport flight domain in C-band (802.16e). Details of the evaluation criteria, channel models, and the technology evaluations are provided in appendixes

Parametric region-based foreround segmentation in planar and multi-view sequences

Foreground segmentation in video sequences is an important area of the image processing that attracts great interest among the scientist community, since it makes possible the detection of the objects that appear in the sequences under analysis, and allows us to achieve a correct performance of high level applications which use foreground segmentation as an initial step. The current Ph.D. thesis entitled Parametric Region-Based Foreground Segmentation in Planar and Multi-View Sequences details, in the following pages, the research work carried out within this eld. In this investigation, we propose to use parametric probabilistic models at pixel-wise and region level in order to model the di erent classes that are involved in the classi cation process of the di erent regions of the image: foreground, background and, in some sequences, shadow. The development is presented in the following chapters as a generalization of the techniques proposed for objects segmentation in 2D planar sequences to 3D multi-view environment, where we establish a cooperative relationship between all the sensors that are recording the scene. Hence, di erent scenarios have been analyzed in this thesis in order to improve the foreground segmentation techniques: In the first part of this research, we present segmentation methods appropriate for 2D planar scenarios. We start dealing with foreground segmentation in static camera sequences, where a system that combines pixel-wise background model with region-based foreground and shadow models is proposed in a Bayesian classi cation framework. The research continues with the application of this method to moving camera scenarios, where the Bayesian framework is developed between foreground and background classes, both characterized with region-based models, in order to obtain a robust foreground segmentation for this kind of sequences. The second stage of the research is devoted to apply these 2D techniques to multi-view acquisition setups, where several cameras are recording the scene at the same time. At the beginning of this section, we propose a foreground segmentation system for sequences recorded by means of color and depth sensors, which combines di erent probabilistic models created for the background and foreground classes in each one of the views, by taking into account the reliability that each sensor presents. The investigation goes ahead by proposing foreground segregation methods for multi-view smart room scenarios. In these sections, we design two systems where foreground segmentation and 3D reconstruction are combined in order to improve the results of each process. The proposals end with the presentation of a multi-view segmentation system where a foreground probabilistic model is proposed in the 3D space to gather all the object information that appears in the views. The results presented in each one of the proposals show that the foreground segmentation and also the 3D reconstruction can be improved, in these scenarios, by using parametric probabilistic models for modeling the objects to segment, thus introducing the information of the object in a Bayesian classi cation framework.La segmentaci on de objetos de primer plano en secuencias de v deo es una importante area del procesado de imagen que despierta gran inter es por parte de la comunidad cient ca, ya que posibilita la detecci on de objetos que aparecen en las diferentes secuencias en an alisis, y permite el buen funcionamiento de aplicaciones de alto nivel que utilizan esta segmentaci on obtenida como par ametro de entrada. La presente tesis doctoral titulada Parametric Region-Based Foreground Segmentation in Planar and Multi-View Sequences detalla, en las p aginas que siguen, el trabajo de investigaci on desarrollado en este campo. En esta investigaci on se propone utilizar modelos probabil sticos param etricos a nivel de p xel y a nivel de regi on para modelar las diferentes clases que participan en la clasi caci on de las regiones de la imagen: primer plano, fondo y en seg un que secuencias, las regiones de sombra. El desarrollo se presenta en los cap tulos que siguen como una generalizaci on de t ecnicas propuestas para la segmentaci on de objetos en secuencias 2D mono-c amara, al entorno 3D multi-c amara, donde se establece la cooperaci on de los diferentes sensores que participan en la grabaci on de la escena. De esta manera, diferentes escenarios han sido estudiados con el objetivo de mejorar las t ecnicas de segmentaci on para cada uno de ellos: En la primera parte de la investigaci on, se presentan m etodos de segmentaci on para escenarios monoc amara. Concretamente, se comienza tratando la segmentaci on de primer plano para c amara est atica, donde se propone un sistema completo basado en la clasi caci on Bayesiana entre el modelo a nivel de p xel de nido para modelar el fondo, y los modelos a nivel de regi on creados para modelar los objetos de primer plano y la sombra que cada uno de ellos proyecta. La investigaci on prosigue con la aplicaci on de este m etodo a secuencias grabadas mediante c amara en movimiento, donde la clasi caci on Bayesiana se plantea entre las clases de fondo y primer plano, ambas caracterizadas con modelos a nivel de regi on, con el objetivo de obtener una segmentaci on robusta para este tipo de secuencias. La segunda parte de la investigaci on, se centra en la aplicaci on de estas t ecnicas mono-c amara a entornos multi-vista, donde varias c amaras graban conjuntamente la misma escena. Al inicio de dicho apartado, se propone una segmentaci on de primer plano en secuencias donde se combina una c amara de color con una c amara de profundidad en una clasi caci on que combina los diferentes modelos probabil sticos creados para el fondo y el primer plano en cada c amara, a partir de la fi abilidad que presenta cada sensor. La investigaci on prosigue proponiendo m etodos de segmentaci on de primer plano para entornos multi-vista en salas inteligentes. En estos apartados se diseñan dos sistemas donde la segmentaci on de primer plano y la reconstrucci on 3D se combinan para mejorar los resultados de cada uno de estos procesos. Las propuestas fi nalizan con la presentaci on de un sistema de segmentaci on multi-c amara donde se centraliza la informaci on del objeto a segmentar mediante el diseño de un modelo probabil stico 3D. Los resultados presentados en cada uno de los sistemas, demuestran que la segmentacion de primer plano y la reconstrucci on 3D pueden verse mejorados en estos escenarios mediante el uso de modelos probabilisticos param etricos para modelar los objetos a segmentar, introduciendo as la informaci on disponible del objeto en un marco de clasi caci on Bayesiano