Finding the best viewpoints for three-dimensional graph drawings

Eades, Peter; Houle, Michael E.; Webber, Richard L.

doi:10.1007/3-540-63938-1_53

Cited by 21 publications

(21 citation statements)

References 17 publications

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“…So the scene watch the ball created in the system, make its objects, surrounded by projection sphere radius size of stadia, set a certain number of points on a sphere, represent different viewpoints, point to the direction of its coordinates for the projection direction. In the second, literature [10,11] based on point location of 3d scene observation, there made improvements, sphere radius can be changed in the practical application, spherical coordinate points can pick up means point location, the projection direction can change, people can get different projection effect, greatly enhance the experimental efficiency and user interactivity.…”

Section: Technical Solutionmentioning

confidence: 99%

Analysis and Research of Dynamic Observation Transformation Based on the Size of 3D Scene

Chen¹

2017

Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)

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Abstract. In the actual project, when the three-dimensional scene is observed, the three-dimensional scene and the observer appear in the different observation matrix (viewpoint position, projection center and its upward direction), because the size of the observed object is not completely surrounded. Dislocation relationship, resulting in the view display is missing, not the ideal projection view, to the development of the system to bring confusion and interference. Therefore put forward a feasible method: in the first place, according to the actual size of 3d scene, define a completely view sphere to surround the scene, spherical reference point as the point of view, its center point as center of view, this two points decided the projection direction; Finally on the projection direction, according to the 3d scene actual size y determining the minimum observation volume to surround the 3d scene. Experimental results show that the transformation method for 3d scene observation, can easily determine the view matrix and projection matrix, improve the efficiency of the development of 3d graphics system.

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Section: Technical Solutionmentioning

confidence: 99%

Analysis and Research of Dynamic Observation Transformation Based on the Size of 3D Scene

Chen¹

2017

Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)

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“…This becomes apparent when the number of connections is so high that visualizing the network as a graph leads to confusing "spaghetti-like" clusters that are so dense as to not be amendable to interpretation [6]. Furthermore, while algorithms like Kamada-Kawai can be extended to three dimensions, the problem of determining where precisely a user should be placed in the 3-D visualization remains an open area of research [8]. Placing the user's view point "in the middle" of a three-dimensional visualization may hinder rather than help the visualization process, since the viewpoint may hide parts of the network.…”

Section: Network Layoutmentioning

confidence: 99%

Exploring Semantic Social Networks Using Virtual Reality

Halpin

Zielinski

Brady

et al. 2008

Lecture Notes in Computer Science

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Abstract. We present Redgraph, the first generic virtual reality visualization program for Semantic Web data. Redgraph is capable of handling large data-sets, as we demonstrate on social network data from the U.S. Patent Trade Office. We develop a Semantic Web vocabulary of virtual reality terms compatible with GraphXML to map graph visualization into the Semantic Web itself. Our approach to visualizing Semantic Web data takes advantage of user-interaction in an immersive environment to bypass a number of difficult issues in 3-dimensional graph visualization layout by relying on users themselves to interactively extrude the nodes and links of a 2-dimensional graph into the third dimension. When users touch nodes in the virtual reality environment, they retrieve data formatted according to the data's schema or ontology. We applied Redgraph to social network data constructed from patents, inventors, and institutions from the United States Patent and Trademark Office in order to explore networks of innovation in computing. Using this data-set, results of a user study comparing extrusion (3-D) vs. no-extrusion (2-D) are presented. The study showed the use of a 3-D interface by subjects led to significant improvement on answering of fine-grained questions about the data-set, but no significant difference was found for broad questions about the overall structure of the data. Furthermore, inference can be used to improve the visualization, as demonstrated with a data-set of biotechnology patents and researchers.

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“…An exact algorithm that requires a preprocessing time of Ω((|V |+|E|) 4 log(|V |+|E|)) was suggested in [6]. Iterative heuristic algorithms, with a faster running time (but still, at least O(|V | · |E|)), were suggested in [13].…”

Section: Finding the Best Viewpoint For 3-d Layoutsmentioning

confidence: 99%

Graph Drawing by High-Dimensional Embedding

Harel¹,

Koren²

2006

Graph Algorithms and Applications 5

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We present a novel approach to the aesthetic drawing of undirected graphs. The method has two phases: first embed the graph in a very high dimension and then project it into the 2-D plane using principal components analysis. Running time is linear in the graph size, and experiments we have carried out show the ability of the method to draw graphs of 10 5 nodes in few seconds. The new method appears to have several advantages over classical methods, including a significantly better running time, a useful inherent capability to exhibit the graph in various dimensions, and an effective means for interactive exploration of large graphs.

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Finding the best viewpoints for three-dimensional graph drawings

Cited by 21 publications

References 17 publications

Analysis and Research of Dynamic Observation Transformation Based on the Size of 3D Scene

Analysis and Research of Dynamic Observation Transformation Based on the Size of 3D Scene

Exploring Semantic Social Networks Using Virtual Reality

Graph Drawing by High-Dimensional Embedding

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