Abstract
For types of data visualization where the cost of producing images is high, and the relationship between the rendering parameters and the image produced is less than obvious, a visual representation of the exploration process can make the process more efficient and effective. Image graphs represent not only the results but also the process of data visualization. Each node in an image graph consists of an image and the corresponding visualization parameters used to produce it. Each edge in a graph shows the change in rendering parameters between the two nodes it connects. Image graphs are not just static representations: users can interact with a graph to review a previous visualization session or to perform new rendering. Operations which cause changes in rendering parameters can propagate through the graph. The user can take advantage of the information in image graphs to understand how certain parameter changes affect visualization results. Users can also share image graphs to streamline the process of collaborative visualization. We have implemented a volume visualization system using the image graph interface, and our examples in the paper come from this application.
| Original language | English (US) |
|---|---|
| Pages | 81-88 |
| Number of pages | 8 |
| State | Published - Dec 1 1999 |
| Event | Proceedings of the IEEE Visualization '99 - San Francisco, CA, USA Duration: Oct 24 1999 → Oct 29 1999 |
Other
| Other | Proceedings of the IEEE Visualization '99 |
|---|---|
| City | San Francisco, CA, USA |
| Period | 10/24/99 → 10/29/99 |
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ASJC Scopus subject areas
- Computer Science(all)
- Engineering(all)
Cite this
Image graphs - a novel approach to visual data exploration. / Ma, Kwan-Liu.
1999. 81-88 Paper presented at Proceedings of the IEEE Visualization '99, San Francisco, CA, USA, .Research output: Contribution to conference › Paper
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T1 - Image graphs - a novel approach to visual data exploration
AU - Ma, Kwan-Liu
PY - 1999/12/1
Y1 - 1999/12/1
N2 - For types of data visualization where the cost of producing images is high, and the relationship between the rendering parameters and the image produced is less than obvious, a visual representation of the exploration process can make the process more efficient and effective. Image graphs represent not only the results but also the process of data visualization. Each node in an image graph consists of an image and the corresponding visualization parameters used to produce it. Each edge in a graph shows the change in rendering parameters between the two nodes it connects. Image graphs are not just static representations: users can interact with a graph to review a previous visualization session or to perform new rendering. Operations which cause changes in rendering parameters can propagate through the graph. The user can take advantage of the information in image graphs to understand how certain parameter changes affect visualization results. Users can also share image graphs to streamline the process of collaborative visualization. We have implemented a volume visualization system using the image graph interface, and our examples in the paper come from this application.
AB - For types of data visualization where the cost of producing images is high, and the relationship between the rendering parameters and the image produced is less than obvious, a visual representation of the exploration process can make the process more efficient and effective. Image graphs represent not only the results but also the process of data visualization. Each node in an image graph consists of an image and the corresponding visualization parameters used to produce it. Each edge in a graph shows the change in rendering parameters between the two nodes it connects. Image graphs are not just static representations: users can interact with a graph to review a previous visualization session or to perform new rendering. Operations which cause changes in rendering parameters can propagate through the graph. The user can take advantage of the information in image graphs to understand how certain parameter changes affect visualization results. Users can also share image graphs to streamline the process of collaborative visualization. We have implemented a volume visualization system using the image graph interface, and our examples in the paper come from this application.
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