Using cross-talk simulation to predict the performance of anaglyph 3-D glasses

The anaglyph 3-D method is a widely used technique for presenting stereoscopic 3-D images. Its primary advantage is that it will work on any full-color display (LCDs, plasmas, and even prints) and only requires that the user view the anaglyph image using a pair of anaglyph 3-D glasses with usually one lens tinted red and the other lens tinted cyan (blue plus green). A common image-quality problem of anaglyph 3-D images is high levels of cross-talk — the incomplete isolation of the left and right image channels such that each eye sees a “ghost” of the opposite perspective view. An anaglyph cross-talk simulation model has been developed which allows the amount of anaglyph cross-talk to be estimated based on the spectral characteristics of the anaglyph glasses and the display. The model is validated using a visual cross-talk ranking test which indicates good agreement. The model is then used to consider two scenarios for the reduction of cross-talk in anaglyph systems and finds that a considerable reduction is likely to be achieved by using spectrally pure displays. The study also finds that the 3-D performance of commercial anaglyph glasses can be significantly better than handmade anaglyph glasses

Methods for reducing visual discomfort in stereoscopic 3D: A review

This work was supported by the EPSRC Grant EP/M01469X/1, “Geometric Evaluation of Stereoscopic Video”

3D Visualisierung multivariater Daten

Nowadays large amounts of data are organized in tables, especially in relational databases where the rows store the data items to which multiple attributes are stored in the columns. Information stored this way, having multiple (more than two or three) attributes, can be treated as multivariate data. Therefore, visualization methods for multivariate data have a large application area and high potential utility. This thesis focuses on the application of 3D scatter plots for the visualization of multivariate data. When dealing with 3D, spatial perception needs to be exploited, by effectively using depth cues to convey spatial information to the user. To improve the presentation of individual 3D scatter plots, a technique is presented that applies illumination to them, thus using the shape-from-shading depth cue. To enable the analysis not only of 3D but of multivariate data, a novel technique is introduced that allows the navigation between 3D scatter plots. Inspecting the large number of 3D scatter plots that can be projected from a multivariate data set is very time consuming. The analysis of multivariate data can benefit from automatic machine learning approaches. A presented method uses decision trees to increase the speed a user can gain an understanding of the multivariate data at no extra cost. Stereopsis can also support the display of 3D scatter plots. Here an improved anaglyph rendering technique is presented, significantly reducing ghosting artifacts. The technique is not only applicable for information visualization, but for general rendering or to present stereoscopic image data. Some information visualization algorithms require high computation time. Many of these algorithms can be parallelized to run interactively. A framework that supports the parallelization on shared and distributed memory systems is presented.In der heutigen Zeit werden große Datenmengen in Tabellen gespeichert, vor allem in relationalen Datenbanken. Dort speichern die Zeilen die Datensätze und die Spalten unterschiedliche Datenattribute. Informationen, die so gespeichert sind, können als multivariate Daten behandelt werden. Daher haben Visualisierungsmethoden für multivariate Daten ein breites Anwendungsgebiet und hohen potentiellen Nutzen. Diese Arbeit hat die Anwendung von 3D Streudiagrammen zur Visualisierung multivariater Daten zum Fokus. Wenn dreidimensionale Objekte verwendet werden, muss die dreidimensionale Struktur durch den effektiven Einsatz von Hinweisreizen für das Tiefensehen (engl. depth cues) dem Betrachter vermittelt werden. Um die Darstellung einzelner 3D Streudiagramme zu verbessern, wird ein Verfahren vorgestellt, welches Beleuchtung auf diese anwendet und dadurch den gleichnamigen Hinweisreiz verwendet. Um die Analyse von nicht nur dreidimensionalen, sondern auch multivariaten Daten zu ermöglichen, wird ein neues Verfahren vorgestellt, welches die Navigation zwischen 3D Streudiagrammen ermöglicht. Eine große Anzahl von 3D Streudiagrammen zu untersuchen ist sehr zeitraubend. Die Analyse multivariater Daten kann jedoch von automatischen maschinellen Lernverfahren profitieren. Ein vorgestelltes Verfahren verwendet Entscheidungsbäume, um die Geschwindigkeit zu erhöhen, mit der ein Benutzer multivariate Daten verstehen kann, ohne einen zeitlichen Mehraufwand auf der Seite des Benutzers zu verursachen. Stereopsis kann auch die Anzeige von 3D Streudiagrammen unterstützen. Hier wird ein verbessertes Verfahren zur Erzeugung von Anaglyph-Stereo-Darstellungen vorgestellt, welches Geisterbildartefakte signifikant reduziert. Das Verfahren ist nicht nur in der Informationsvisualisierung, sondern auch generell für Rendering einsetzbar und eignet sich sogar zur Darstellung von stereoskopischen Fotoaufnahmen. Manche Informationsvisualisierungsalgorithmen benötigen viel Rechenzeit. Viele dieser Algorithmen lassen sich mit Hilfe von Parallellisierung interaktiv ausführen. Es wird ein System vorgestellt, welches die Parallelisierung sowohl auf Mehrkernprozessoren als auch verteilt über einem Netwerk unterstützt

Interactively refining object-recognition system

Existing techniques for object recognition often make use of a combination of multiple algorithms and sensors to achieve adequate results. In this paper we propose a real-time system to efficiently combine multiple object-recognition techniques, appropriate for mobile Augmented Reality applications. We focus on the challenge to differentiate objects with only marginal distinguishing features that can often only be identified from specific points of view, and solve this problem by interactively guiding the user during the recognition process. The system is based on a hierarchy to organize model data and control the corresponding feature-detection techniques as shown in a prototypical implementation. Furthermore, recognition techniques are chosen based on context information, e.g. feature type, reliability of sensor data, etc

NexusVIS: A distributed visualization toolkit for mobile applications

Abstract—Many mobile pervasive applications need to visualize information about the user’s geographic surroundings combined with data from sensors, which determine the user’s context. In this demonstration we show NexusVIS, a distributed visualization toolkit for mobile applications. By building upon an existing data stream processing system we enable applications to define distributed visualization processes as continuous queries. This allows applications to define visualization semantics descriptively. Moreover, NexusVIS is capable of adapting the visual query at runtime, and thus allows to navigate in the visualized scene both automatically and manually through user control. I