scholarly journals Augmenting Image Warping-Based Remote Volume Rendering with Ray Tracing

Author(s):  
Stefan Zellmann

<div><div><div><p>We propose an image warping-based remote rendering technique for volumes that decouples the rendering and display phases. Our work builds on prior work that samples the volume on the client using ray casting and reconstructs a z-value based on some heuristic. The color and depth buffer are then sent to the client that reuses this depth image as a stand-in for subsequent frames by warping it according to the current camera position until new data was received from the server. We augment that method by implementing the client renderer using ray tracing. By representing the pixel contributions as spheres, this allows us to effectively vary their footprint based on the distance to the viewer, which we find to give better results than point-based rasterization when applied to volumetric data sets.</p></div></div></div>

2020 ◽  
Author(s):  
Stefan Zellmann

<div><div><div><p>We propose an image warping-based remote rendering technique for volumes that decouples the rendering and display phases. Our work builds on prior work that samples the volume on the client using ray casting and reconstructs a z-value based on some heuristic. The color and depth buffer are then sent to the client that reuses this depth image as a stand-in for subsequent frames by warping it according to the current camera position until new data was received from the server. We augment that method by implementing the client renderer using ray tracing. By representing the pixel contributions as spheres, this allows us to effectively vary their footprint based on the distance to the viewer, which we find to give better results than point-based rasterization when applied to volumetric data sets.</p></div></div></div>


2012 ◽  
Vol 542-543 ◽  
pp. 1434-1437
Author(s):  
Xiao Ping Xiao ◽  
Zi Sheng Li ◽  
Wei Gong

Aiming at the problem that rendering 3D Julia sets on CPU is slowly, a method of rendering 3D Julia sets on GPU is presented in this paper. After introducing the advantages of GPU and the operations of quaternion, the generating process of 3D Julia sets is discussed in detail. Ray tracing volume rendering algorithm is applied to obtain high quality 3D Julia sets, and escaping time algorithm is used to generate the discreet data of Julia sets, of which normal is estimated according to the original of ray and accelerated by using unbounding sphere algorithm, and the graphics examples are given to illustrate this algorithm. Finally, the factors of affecting rendering speed and refined effect are summarized. The results show that the speed of 3D Julia sets rendering on GPU is much faster than CPU, and the interactivity of rendering process is also enhanced.


1997 ◽  
Vol 3 (S2) ◽  
pp. 1131-1132
Author(s):  
Jansma P.L ◽  
M.A. Landis ◽  
L.C. Hansen ◽  
N.C. Merchant ◽  
N.J. Vickers ◽  
...  

We are using Data Explorer (DX), a general-purpose, interactive visualization program developed by IBM, to perform three-dimensional reconstructions of neural structures from microscopic or optical sections. We use the program on a Silicon Graphics workstation; it also can run on Sun, IBM RS/6000, and Hewlett Packard workstations. DX comprises modular building blocks that the user assembles into data-flow networks for specific uses. Many modules come with the program, but others, written by users (including ourselves), are continually being added and are available at the DX ftp site, http://www.tc.cornell.edu/DXhttp://www.nice.org.uk/page.aspx?o=43210.Initally, our efforts were aimed at developing methods for isosurface- and volume-rendering of structures visible in three-dimensional stacks of optical sections of insect brains gathered on our Bio-Rad MRC-600 laser scanning confocal microscope. We also wanted to be able to merge two 3-D data sets (collected on two different photomultiplier channels) and to display them at various angles of view.


Author(s):  
JIANLONG ZHOU ◽  
ZHIYAN WANG ◽  
KLAUS D. TÖNNIES

In this paper, a new approach named focal region-based volume rendering for visualizing internal structures of volumetric data is presented. This approach presents volumetric information through integrating context information as the structure analysis of the data set with a lens-like focal region rendering to show more detailed information. This feature-based approach contains three main components: (i) A feature extraction model using 3D image processing techniques to explore the structure of objects to provide contextual information; (ii) An efficient ray-bounded volume ray casting rendering to provide the detailed information of the volume of interest in the focal region; (iii) The tools used to manipulate focal regions to make this approach more flexible. The approach provides a powerful framework for producing detailed information from volumetric data. Providing contextual information and focal region renditions at the same time has the advantages of easy to understand and comprehend volume information for the scientist. The interaction techniques provided in this approach make the focal region-based volume rendering more flexible and easy to use.


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