Automatic generation of computer graphics languages

1976 ◽  
Author(s):  
Gregory J. Suski
Keyword(s):  
Computer Graphics ◽  
Automatic Generation

Automatic generation of computer graphics languages

1976 ◽  
Vol 11 (6) ◽  
pp. 113-122 ◽  
Author(s):  
Gregory J. Suski
Keyword(s):  
Computer Graphics ◽  
Automatic Generation

scholarly journals Procedural interior generation for artificial intelligence training and computer graphics

2020 ◽  
Author(s):  
Egor Feklisov ◽  
Mihail Zinderenko ◽  
Vladimir Frolov
Keyword(s):  
Computer Graphics ◽  
3D Models ◽  
Automatic Generation ◽  
Machine Learning Algorithms ◽  
Single Person ◽  
Segmentation Algorithms ◽  
Realistic Scenes ◽  
Asset Creation ◽  
And Robotics ◽  
Semantic Database

Since the creation of computers, there has been a lingering problem of data storing and creation for various tasks. In terms of computer graphics and video games, there has been a constant need in assets. Although nowadays the issue of space is not one of the developers' prime concerns, the need in being able to automate asset creation is still relevant. The graphical fidelity, that the modern audiences and applications demand requires a lot of work on the artists' and designers' front, which costs a lot. The automatic generation of 3D scenes is of critical importance in the tasks of Artificial Intelligent (AI) robotics training, where the amount of generated data during training cannot even be viewed by a single person due to the large amount of data needed for machine learning algorithms. A completely separate, but nevertheless necessary task for an integrated solution, is furniture generation and placement, material and lighting randomisation. In this paper we propose interior generator for computer graphics and robotics learning applications. The suggested framework is able to generate and render interiors with furniture at photo-realistic quality. We combined the existing algorithms for generating plans and arranging interiors and then finally add material and lighting randomization. Our solution contains semantic database of 3D models and materials, which allows generator to get realistic scenes with randomization and per-pixel mask for training detection and segmentation algorithms.

Improved 3-D reconstruction using stereo computer graphics and multiple tilt EM images

1995 ◽  
Vol 53 ◽  
pp. 630-631
Author(s):  
Lee D. Peachey ◽  
Lou Fodor ◽  
John C. Haselgrove ◽  
Stanley M. Dunn ◽  
Junqing Huang
Keyword(s):  
Computer Graphics ◽  
High Performance ◽  
Transverse Section ◽  
Three Dimensional ◽  
Stereo Pair ◽  
3D Reconstructions ◽  
Video Cameras ◽  
Biological Objects ◽  
Microscope Images ◽  
High Performance Computer

Stereo pairs of electron microscope images provide valuable visual impressions of the three-dimensional nature of specimens, including biological objects. Beyond this one seeks quantitatively accurate models and measurements of the three dimensional positions and sizes of structures in the specimen. In our laboratory, we have sought to combine high resolution video cameras with high performance computer graphics systems to improve both the ease of building 3D reconstructions and the accuracy of 3D measurements, by using multiple tilt images of the same specimen tilted over a wider range of angles than can be viewed stereoscopically. Ultimately we also wish to automate the reconstruction and measurement process, and have initiated work in that direction.Figure 1 is a stereo pair of 400 kV images from a 1 micrometer thick transverse section of frog skeletal muscle stained with the Golgi stain. This stain selectively increases the density of the transverse tubular network in these muscle cells, and it is this network that we reconstruct in this example.

Stereo modeling of HVEM specimens by serial tilting and computer graphics

1986 ◽  
Vol 44 ◽  
pp. 34-35
Author(s):  
J.R. McIntosh ◽  
D.L. Stemple ◽  
William Bishop ◽  
G.W. Hannaway
Keyword(s):  
Computer Graphics ◽  
Analytical Methods ◽  
Photographic Film ◽  
Complex Structures ◽  
Multiple Objects ◽  
Multiple Images ◽  
3 Dimensional

EM specimens often contain 3-dimensional information that is lost during micrography on a single photographic film. Two images of one specimen at appropriate orientations give a stereo view, but complex structures composed of multiple objects of graded density that superimpose in each projection are often difficult to decipher in stereo. Several analytical methods for 3-D reconstruction from multiple images of a serially tilted specimen are available, but they are all time-consuming and computationally intense.

The Role of Visual Distractors in the Simon Effect

2017 ◽  
Vol 64 (6) ◽  
pp. 387-397 ◽  
Author(s):  
Luisa Lugli ◽  
Stefania D’Ascenzo ◽  
Roberto Nicoletti ◽  
Carlo Umiltà
Keyword(s):  
Simon Effect ◽  
Simon Task ◽  
Automatic Generation ◽  
Spatial Code ◽  
Attentional Model ◽  
Previous Evidence ◽  
Spatial Stimulus ◽  
Attentional Resources ◽  
Code Changes

Abstract. The Simon effect lies on the automatic generation of a stimulus spatial code, which, however, is not relevant for performing the task. Results typically show faster performance when stimulus and response locations correspond, rather than when they do not. Considering reaction time distributions, two types of Simon effect have been individuated, which are thought to depend on different mechanisms: visuomotor activation versus cognitive translation of spatial codes. The present study aimed to investigate whether the presence of a distractor, which affects the allocation of attentional resources and, thus, the time needed to generate the spatial code, changes the nature of the Simon effect. In four experiments, we manipulated the presence and the characteristics of the distractor. Findings extend previous evidence regarding the distinction between visuomotor activation and cognitive translation of spatial stimulus codes in a Simon task. They are discussed with reference to the attentional model of the Simon effect.

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