Edge and corner identification for tracking the line of sight

This article presents an edge-corner detector, implemented in the realm of the GEIST project (an Computer Aided Touristic Information System) to extract the information of straight edges and their intersections (image corners) from camera-captured (real world) and computer-generated images (from the database of Historical Monuments, using observer position and orientation data) -- Camera and computer-generated images are processed for reduction of detail, skeletonization and corner-edge detection -- The corners surviving the detection and skeletonization process from both images are treated as landmarks and fed to a matching algorithm, which estimates the sampling errors which usually contaminate GPS and pose tracking data (fed to the computer-image generatator) -- In this manner, a closed loop control is implemented, by which the system converges to exact determination of position and orientation of an observer traversing a historical scenario (in this case the city of Heidelberg) -- With this exact position and orientation, in the GEIST project other modules are able to project history tales on the view field of the observer, which have the exact intended scenario (the real image seen by the observer) -- In this way, the tourist “sees” tales developing in actual, material historical sites of the city -- To achieve these goals this article presents the modification and articulation of algorithms such as the Canny Edge Detector, SUSAN Corner Detector, 1-D and 2-D filters, etceter

Edge and corner identification for tracking the line of sight

This article presents an edge-corner detector, implemented in the realm of the GEIST project (an Computer Aided Touristic Information System) to extract the information of straight edges and their intersections (image corners) from camera-captured (real world) and computer-generated images (from the database of Historical Monuments, using ob- server position and orientation data). Camera and computer-generated images are processed for reduction of detail, skeletonization and corner-edge detection. The corners surviving the detection and skeletonization process from both images are treated as landmarks and fed to a matching algorithm, which estimates the sampling errors which usually contaminate GPS and pose tracking data (fed to the computer-image generatator).PACS: 07.05.PjMSC: 68Uxx, 68U05, 68U10Este artículo presenta un detector de aristas y esquinas, implementado en el dominio del proyecto GEIST (un Sistema de Información Turística Asistido por Computador) para extraer la información de aristas rectas y sus intersecciones (esquinas en la imagen) a partir de imágenes de cámara (del mundo real) contrastadas con imágenes generadas por computador (de la Base de Datos de Monumentos Históricos a partir de posición y orientación de un observador virtual). Las imágenes de la cámara y las generadas por computador son procesadas para reducir detalle, hallar el esqueleto de la imagen y detectar aristas y esquinas. Las esquinas sobrevivientes del proceso de detección y hallazgo del esqueleto de las imágenes son tratados como puntos referentes y alimentados a un algoritmo de puesta en correspondencia, el cual estima los errores de muestreo que usualmente contaminan los datos de GPS y orientación (alimentados al generador de imágenes por computador). De esta manera, un ciclo de control de lazo cerrado se implementa, por medio del cual el sistema converge a la determinación exacta de posición y orientación de un observador atravesando un escenario histórico (en este caso, la ciudad de Heidelberg). Con esta posición y orientación exactas, en el proyecto GEIST otros módulos son capaces de proyectar re-creaciones históricas en el campo de visión del observador, las cuales tienen el escenario exacto (la imagen real vista por el observador). Así, el turista “ve” las escenas desarrollándose en sitios históricos materiales y reales de la ciudad. Para ello, este artículo presenta la modificación y articulación de algoritmos tales como el Canny Edge Detector, “SUSAN Corner detector”, filtros 1- y 2-dimensionales, etcétera.PACS: 07.05.PjMSC: 68Uxx, 68U05, 68U1

Global Consistency Management within a CAD Framework

Consistency Guarantees the correctness of information. Within a CAD Framework, there are several components which deal with different aspects of consistency management depending on the different tasks of the components. Presently, every component has its own language for the definition of constraints, its own functionality and its own mechanism for the evaluation of constraints. This paper presents the idea of a global consistency management system within a CAD Framework. It presents the different aspects of consistency related to the different components of a CAD Framework and offers strategies for defining and administering constraints in a uniform way. (IGD

Eine offene, verteilte CAD-System Umgebung zur Unterstützung von Concurrent Engineering : Konzept für einen Konsistenz-Manager

Basierend auf einer Analyse aktueller Entwicklungen im Bereich von CAD-Umgebungen werden in dieser Arbeit Konzepte definiert und in eine Gesamtarchitektur homogen integriert, die besonders bei den identifizierten Problembereichen eine Unterstützung bieten. Ein Konsistenz-Manager wird als Querschnittsdienst spezifiziert und in diesem Kontext die grundlegenden Konzepte zur Wahrung der Konsistenz vorgestellt. Die speziellen Anforderungen an solch einen Dienst im Sinne einer Umgebung zur Unterstützung des Concurrent Engineerings wurden hierbei berücksichtigt

Eine offene, verteilte CAD-System Umgebung zur Unterstützung von Concurrent Engineering: Konzept für einen Konsistenz-Manager

Basierend auf einer Analyse aktueller Entwicklungen im Bereich von CAD-Umgebungen werden in dieser Arbeit Konzepte definiert und in eine Gesamtarchitektur homogen integriert, die besonders bei den identifizierten Problembereichen eine Unterstützung bieten. Ein Konsistenz-Manager wird als Querschnittsdienst spezifiziert und in diesem Kontext die grundlegenden Konzepte zur Wahrung der Konsistenz vorgestellt. Die speziellen Anforderungen an solch einen Dienst im Sinne einer Umgebung zur Unterstützung des Concurrent Engineerings wurden hierbei berücksichtigt

Visualization techniques in metadata information systems for geospatial data

This paper describes MIS in general and presents — by means of an information system for residual waste — several approaches to overcome the lack of usability in these information systems for environmental and geospatial data. MetaViz uses visualization techniques and spatial metaphors to generate effective and intuitive representations of the metadata. InfoCrystal is settled in the field of mathematics and tries to facilitate the query formulation and query refinement process by using abstract Venn diagrams instead of traditional fill-in forms. VisDB and TileBars are two approaches which have originated in the field of visual data mining/exploration, aimed at visualizing as much information as possible. Finally, some suggestions for further research in that field are described. The more information and data2 that are produced in the actual information society, the more important mechanisms and systems which organize the data and include information on where to find these data become. Most popular peculiarities of such information systems are digital libraries, metadata3 information systems (MIS) and catalogue systems (CS). Recent initiatives to geospatial libraries and environmental MIS/CS provide access to a wealth of distributed data, but offer only basic levels of interactivity and user assistance. This includes all steps of the information retrieval process: query formulation, query modification, comparison of (metadata) result sets and detailed presentation with respect to the visualization of result sets