Andere Kunden interessierten sich auch für
![Understanding Virtual Reality as a Tool for Experimental Research in Information Systems. The Case of Application Strategies: Exploring the Why, How, and When of Utilizing Virtual Reality in Information Systems Research]( "Understanding Virtual Reality as a Tool for Experimental Research in Information Systems. The Case of Application Strategies: Exploring the Why, How, and When of Utilizing Virtual Reality in Information Systems Research")
Understanding Virtual Reality as a Tool for Experimental Research in Information Systems. The Case of Application Strategies: Exploring the Why, How, and When of Utilizing Virtual Reality in Information Systems Research54,78 €![UNHACKABLE]( "UNHACKABLE")
UNHACKABLE18,99 €![Practical Predictive Analytics]( "Practical Predictive Analytics")
Practical Predictive Analytics54,99 €![Predictive Data Mining]( "Predictive Data Mining")
Predictive Data Mining50,99 €![Predictive Analysis on Large Data for Actionable Knowledge]( "Predictive Analysis on Large Data for Actionable Knowledge")
Predictive Analysis on Large Data for Actionable Knowledge125,99 €![Mastering Predictive Analytics with scikit-learn and TensorFlow]( "Mastering Predictive Analytics with scikit-learn and TensorFlow")
Mastering Predictive Analytics with scikit-learn and TensorFlow35,99 €![Mastering Predictive Analytics with R, Second Edition]( "Mastering Predictive Analytics with R, Second Edition")
Mastering Predictive Analytics with R, Second Edition53,99 €
Radiometrically correct images are extremely important for Virtual Reality applications like Virtual Design, where users need to make decisions impacting large investments based on simulations. Unfortunately, generation of such imagery is still an unsolved problem due to manifold reasons. First, rendered scenes are not modeled accurately enough. Second, even with huge computational efforts existing rendering algorithms lack sufficient precision. Third, current display devices convert rendered images into low-dimensional color spaces, which prohibits display of radiometrically correct results. Overcoming these limitations is the focus of current state-of-the-art research. This thesis also contributes to this task. First, it briefly introduces the necessary background and identifies the steps required for real-time predictive image generation. Then, existing techniques targeting these steps are presented. To solve some of the remaining problems, novel techniques are proposed. They cover various steps in the predictive image generation process, ranging from accurate scene modeling over efficient data representation to high-quality, real-time rendering.