Graphics

About: Graphics is a research topic. Over the lifetime, 17394 publications have been published within this topic receiving 411468 citations. The topic is also known as: graphic.

Three varieties of realism in computer graphics

Abstract: This paper describes three varieties of realism that need to be considered in evaluating computer graphics images and defines the criteria that need to be met if each kind of realism is to be achieved. The paper introduces a conceptual framework for thinking about realism in images, and describes a set of research tools for measuring image realism and assessing its value in graphics applications.

semPlot: Unified Visualizations of Structural Equation Models

Abstract: Structural equation modeling (SEM) has a long history of representing models graphically as path diagrams. This article presents the freely available semPlot package for R, which fills the gap between advanced, but time-consuming, graphical software and the limited graphics produced automatically by SEM software. In addition, semPlot offers more functionality than drawing path diagrams: It can act as a common ground for importing SEM results into R. Any result usable as input to semPlot can also be represented in any of the 3 popular SEM frameworks, as well as translated to input syntax for the R packages sem (Fox, Nie, & Byrnes, 2013) and lavaan (Rosseel, 2012). Special considerations are made in the package for the automatic placement of variables, using 3 novel algorithms that extend the earlier work of Boker, McArdle, and Neale (2002). The article concludes with detailed instructions on these node-placement algorithms.

Real-time image generation system for simulating physical paint, drawing media, and feature modeling with 3-d graphics

Abstract: A computer graphics painting system (A) defined in terms of three-dimensional graphics and texturing mapping. A three-dimensional drawing primitive, most commonly a polygonal mesh (24), is directed along a path (S1) specified by a tablet (T), mouse, or other input stream (P). The primitive is transformed to sequential locations along the stroke in three-dimensional space. In one embodiment, at each location the primitive is processed with texture mapping techniques and blended into the frame buffer (21, 58 and 116) for real-time display. In another embodiment, the primitive is defined by characteristic information assigned at the primitive's vertices (126a, 126b and 126c). In another embodiment, the primitive's vertex information is obtained by retrieving the information from a map. The brush primitive may take many forms to achieve a wide variety of painting effects and styles. The polygonal mesh form may also be active in conforming to any underlying surface or model data, thus enabling real-time painting of three-dimensional objects.

Mathematica: A system for doing mathematics by computer

Abstract: Mathematica is a computer software system for symbolic manipulation and numerical computation; it has excellent graphics, a high-level, mathematically-oriented programming language and, very importantly, it takes seriously the need for work to be interactive, properly presented and communicated. This article is in fact prepared as a Mathematica “notebook”. An extensive library of supporting software “packages” has been developed, and several books about using it are now available.

Fast and approximate stream mining of quantiles and frequencies using graphics processors

Abstract: We present algorithms for fast quantile and frequency estimation in large data streams using graphics processors (GPUs). We exploit the high computation power and memory bandwidth of graphics processors and present a new sorting algorithm that performs rasterization operations on the GPUs. We use sorting as the main computational component for histogram approximation and construction of e-approximate quantile and frequency summaries. Our algorithms for numerical statistics computation on data streams are deterministic, applicable to fixed or variable-sized sliding windows and use a limited memory footprint. We use GPU as a co-processor and minimize the data transmission between the CPU and GPU by taking into account the low bus bandwidth. We implemented our algorithms on a PC with a NVIDIA GeForce FX 6800 Ultra GPU and a 3.4 GHz Pentium IV CPU and applied them to large data streams consisting of more than 100 million values. We also compared the performance of our GPU-based algorithms with optimized implementations of prior CPU-based algorithms. Overall, our results demonstrate that the graphics processors available on a commodity computer system are efficient stream-processor and useful co-processors for mining data streams.