The application visualization system: a computational environment for scientific visualization

1989 ◽  
Vol 9 (4) ◽  
pp. 30-42 ◽  
Author(s):  
C. Upson ◽  
T.A. Faulhaber ◽  
D. Kamins ◽  
D. Laidlaw ◽  
D. Schlegel ◽  
...  
SMPTE Journal ◽  
1995 ◽  
Vol 104 (3) ◽  
pp. 125-133 ◽  
Author(s):  
David A. Epstein ◽  
Sherman R. Alpert ◽  
Inching Chen

2008 ◽  
Vol 266 (9) ◽  
pp. 1475-1487 ◽  
Author(s):  
G. Strauß ◽  
N. Bahrami ◽  
M. Hofer ◽  
E. Dittrich ◽  
M. Strauß ◽  
...  

Kybernetes ◽  
2008 ◽  
Vol 37 (9/10) ◽  
pp. 1530-1541 ◽  
Author(s):  
Olusegun Folorunso ◽  
Oluwafemi Shawn Ogunseye

Author(s):  
P. Hübner ◽  
M. Weinmann ◽  
M. Hillemann ◽  
B. Jutzi ◽  
S. Wursthorn

The basic requirement for the successful deployment of a mobile augmented reality application is a reliable tracking system with high accuracy. Recently, a helmet-based inside-out tracking system which meets this demand has been proposed for self-localization in buildings. To realize an augmented reality application based on this tracking system, a display has to be added for visualization purposes. Therefore, the relative pose of this visualization platform with respect to the helmet has to be tracked. In the case of hand-held visualization platforms like smartphones or tablets, this can be achieved by means of image-based tracking methods like marker-based or model-based tracking. In this paper, we present two marker-based methods for tracking the relative pose between the helmet-based tracking system and a tablet-based visualization system. Both methods were implemented and comparatively evaluated in terms of tracking accuracy. Our results show that mobile inside-out tracking systems without integrated displays can easily be supplemented with a hand-held tablet as visualization device for augmented reality purposes.


2020 ◽  
Author(s):  
David Saffo ◽  
Aristotelis Leventidis ◽  
Twinkle Jain ◽  
Michelle Borkin ◽  
Cody Dunne

Autonomous unmanned aerial vehicles are complex systems of hardware, software, and human input. Understanding this complexity is key to their development and operation. Information visualizations already exist for exploring flight logs but comprehensive analyses currently require several disparate and custom tools. This design study helps address the pain points faced by autonomous unmanned aerial vehicle developers and operators. We contribute: a spiral development process model for grounded evaluation visualization development focused on progressively broadening target user involvement and refining user goals; a demonstration of the model as part of developing a deployed and adopted visualization system; a data and task abstraction for developers and operators performing post-flight analysis of autonomous unmanned aerial vehicle logs; the design and implementation of DATA COMETS, an open-source and web-based interactive visualization tool for post-flight log analysis incorporating temporal, geospatial, and multivariate data; and the results of a summative evaluation of the visualization system and our abstractions based on in-the-wild usage. A free copy of this paper and source code are available at osf.io/h4p7g


Author(s):  
Trefor Williams ◽  
John Betak

The objective of this paper is to demonstrate how GIS and data visualization systems can be used to identify spatial relationships to add to our understanding of railroad accident factors. Examples are given of the spatial analysis of broken rail accidents and grade crossing accidents on GIS maps. Additionally, using the Weave data visualization system a data dashboard was constructed that shows the complex interaction between variables like track type, FRA track classification, train speed and track density with broken rail accident causes. The findings indicate that broken rail accidents occur most frequently in the Midwest. Possibly this trend is related to climate change and increased temperatures and precipitation in the United States. GIS visualizations also showed that many truck-trailer accidents at grade crossings occur in low population areas. This work indicates that GIS and data visualizations are a useful method of identifying trends in railroad accidents.


Sign in / Sign up

Export Citation Format

Share Document