Quasiconvex Programming

We define quasiconvex programming, a form of generalized linear programming in which one seeks the point minimizing the pointwise maximum of a collection of quasiconvex functions. We survey algorithms for solving quasiconvex programs either numerically or via generalizations of the dual simplex method from linear programming, and describe varied applications of this geometric optimization technique in meshing, scientific computation, information visualization, automated algorithm analysis, and robust statistics.Comment: 33 pages, 14 figure

A multi-projector CAVE system with commodity hardware and gesture-based interaction

Spatially-immersive systems such as CAVEs provide users with surrounding worlds by projecting 3D models on multiple screens around the viewer. Compared to alternative immersive systems such as HMDs, CAVE systems are a powerful tool for collaborative inspection of virtual environments due to better use of peripheral vision, less sensitivity to tracking errors, and higher communication possibilities among users. Unfortunately, traditional CAVE setups require sophisticated equipment including stereo-ready projectors and tracking systems with high acquisition and maintenance costs. In this paper we present the design and construction of a passive-stereo, four-wall CAVE system based on commodity hardware. Our system works with any mix of a wide range of projector models that can be replaced independently at any time, and achieves high resolution and brightness at a minimum cost. The key ingredients of our CAVE are a self-calibration approach that guarantees continuity across the screen, as well as a gesture-based interaction approach based on a clever combination of skeletal data from multiple Kinect sensors.Preprin

IMPROVE: collaborative design review in mobile mixed reality

In this paper we introduce an innovative application designed to make collaborative design review in the architectural and automotive domain more effective. For this purpose we present a system architecture which combines variety of visualization displays such as high resolution multi-tile displays, TabletPCs and head-mounted displays with innovative 2D and 3D Interaction Paradigms to better support collaborative mobile mixed reality design reviews. Our research and development is motivated by two use scenarios: automotive and architectural design review involving real users from Page\Park architects and FIAT Elasis. Our activities are supported by the EU IST project IMPROVE aimed at developing advanced display techniques, fostering activities in the areas of: optical see-through HMD development using unique OLED technology, marker-less optical tracking, mixed reality rendering, image calibration for large tiled displays, collaborative tablet-based and projection wall oriented interaction and stereoscopic video streaming for mobile users. The paper gives an overview of the hardware and software developments within IMPROVE and concludes with results from first user tests

Two calibration models for compensation of the individual elements properties of self-emitting displays

In this paper, we examine the applicability limits of different methods of compensation of the individual properties of self-emitting displays with significant non-uniformity of chromaticity and maximum brightness. The aim of the compensation is to minimize the perceived image non-uniformity. Compensation of the displayed image non-uniformity is based on minimizing the perceived distance between the target (ideally displayed) and the simulated image displayed by the calibrated screen. The S-CIELAB model of the human visual system properties is used to estimate the perceived distance between two images. In this work, we compare the efficiency of the channel-wise and linear (with channel mixing) compensation models depending on the models of variation in the characteristics of display elements (subpixels). It was found that even for a display with uniform chromatic subpixels characteristics, the linear model with channel mixing is superior in terms of compensation accuracy.This work was supported by Russian Science Foundation (Project No. 20-61-47089)

Imaging methods for understanding and improving visual training in the geosciences

Experience in the field is a critical educational component of every student studying geology. However, it is typically difficult to ensure that every student gets the necessary experience because of monetary and scheduling limitations. Thus, we proposed to create a virtual field trip based off of an existing 10-day field trip to California taken as part of an undergraduate geology course at the University of Rochester. To assess the effectiveness of this approach, we also proposed to analyze the learning and observation processes of both students and experts during the real and virtual field trips. At sites intended for inclusion in the virtual field trip, we captured gigapixel resolution panoramas by taking hundreds of images using custom built robotic imaging systems. We gathered data to analyze the learning process by fitting each geology student and expert with a portable eye- tracking system that records a video of their eye movements and a video of the scene they are observing. An important component of analyzing the eye-tracking data requires mapping the gaze of each observer into a common reference frame. We have made progress towards developing a software tool that helps automate this procedure by using image feature tracking and registration methods to map the scene video frames from each eye-tracker onto a reference panorama for each site. For the purpose of creating a virtual field trip, we have a large scale semi-immersive display system that consists of four tiled projectors, which have been colorimetrically and photometrically calibrated, and a curved widescreen display surface. We use this system to present the previously captured panoramas, which simulates the experience of visiting the sites in person. In terms of broader geology education and outreach, we have created an interactive website that uses Google Earth as the interface for visually exploring the panoramas captured for each site

Perception and Mitigation of Artifacts in a Flat Panel Tiled Display System

Flat panel displays continue to dominate the display market. Larger, higher resolution flat panel displays are now in demand for scientific, business, and entertainment purposes. Manufacturing such large displays is currently difficult and expensive. Alternately, larger displays can be constructed by tiling smaller flat panel displays. While this approach may prove to be more cost effective, appropriate measures must be taken to achieve visual seamlessness and uniformity. In this project we conducted a set of experiments to study the perception and mitigation of image artifacts in tiled display systems. In the first experiment we used a prototype tiled display to investigate its current viability and to understand what critical perceptible visual artifacts exist in this system. Based on word frequencies of the survey responses, the most disruptive artifacts perceived were ranked. On the basis of these findings, we conducted a second experiment to test the effectiveness of image processing algorithms designed to mitigate some of the most distracting artifacts without changing the physical properties of the display system. Still images were processed using several algorithms and evaluated by observers using magnitude scaling. Participants in the experiment noticed statistically significant improvement in image quality from one of the two algorithms. Similar testing should be conducted to evaluate the effectiveness of the algorithms on video content. While much work still needs to be done, the contributions of this project should enable the development of an image processing pipeline to mitigate perceived artifacts in flat panel display systems and provide the groundwork for extending such a pipeline to realtime applications

Adobe Illustrator CS2 crash course

Introdução ao Adobe Illustrator.Compilação de informações, links e tutorial passo-a-passo para a iniciação a este softwareFBAUP, Pedro Amado, 2007-01-22Versão 0.1 (alfa). Actualizada em 2007-01-22.Este trabalho está licenciado sob uma Licença Creative Commons Atribuição-Uso Não-Comercial-Partilha nos termos da mesma Licença 2.5 Portugal. Para ver uma cópia destalicença, visite http://creativecommons.org/licenses/by-nc-sa/2.5/pt/ ou envie uma cartapara Creative Commons, 559 Nathan Abbott Way, Stanford, California 94305, USA.Introduction to Adobe Illustrator.A compilation of informations, links and step-by-step tutorial on adopting adobe Illustrator.FBAUP, Pedro Amado, 2007-01-22Versão 0.1 (alfa). Actualizada em 2007-01-22.Este trabalho está licenciado sob uma Licença Creative Commons Atribuição-Uso Não-Comercial-Partilha nos termos da mesma Licença 2.5 Portugal. Para ver uma cópia destalicença, visite http://creativecommons.org/licenses/by-nc-sa/2.5/pt/ ou envie uma cartapara Creative Commons, 559 Nathan Abbott Way, Stanford, California 94305, USA.<p

Evaluating and Improving Image Quality of Tiled Displays

Tiled displays are created by grouping multiple displays together to form one very large display. These tiled displays are often the only suitable option for displaying very large images but suffer from a grid distortion caused by gaps between each sub-display’s active region. This grid distortion is fundamentally different from other, well-studied, image distortions (e.g., blur, noise, compression) and the impact of these grid distortions has thus far not been studied. This research addresses this lack of attention by investigating the grid distortion’s quality impact and creating perceptual algorithms to reduce this impact. We measure the quality impact of the grid distortion by creating two new image quality assessment (IQA) databases for tiled images. These databases provide significant insight into the unique characteristics of the grid distortion and provide a baseline against which to measure the performance of current IQA metrics. We use these databases to show that current metrics do not adequately reflect the quality impact of the grid distortions, and we create a new metric specifically for tiled images that statistically (with 95% confidence) outperforms current metrics. We improve perceived tiled display image quality by creating new image-correction algorithms based on elements of the human visual system (HVS). These correction techniques modify the perceived quality of the displayed images without directly modifying the static grid distortion. These algorithms are shown, through the use of a third subjective user study, to clearly and consistently improve the perceived quality of tiled images.1 yea