Abstract
It has been known for some time that larger graphs can be interpreted if laid out in 3D and displayed with stereo and/or motion depth cues to support spatial perception. However, prior studies were carried out using displays that provided a level of detail far short of what the human visual system is capable of resolving. Therefore, we undertook a graph comprehension study using a very high resolution stereoscopic display. In our first experiment, we examined the effect of stereoscopic display, kinetic depth, and using 3D tubes versus lines to display the links. The results showed a much greater benefit for 3D viewing than previous studies. For example, with both motion and stereoscopic depth cues, unskilled observers could see paths between nodes in 333 node graphs with less than a 10% error rate. Skilled observers could see up to a 1000-node graph with less than a 10% error rate. This represented an order of magnitude increase over 2D display. In our second experiment, we varied both nodes and links to understand the constraints on the number of links and the size of graph that can be reliably traced. We found the difference between number of links and number of nodes to best account for error rates and suggest that this is evidence for a “perceptual phase transition.” These findings are discussed in terms of their implications for information display.
- Arthur, K., Booth, K. S., and Ware, C. 1993. Evaluating human performance for fishtank virtual reality. ACM Transactions on Information Systems 11, 3, 239--265. Google ScholarDigital Library
- Bollobas, B. 2001. Random Graphs, 2nd Ed., Theorem 6.19, Cambridge Univ. Press, 151.Google Scholar
- Campbell, F. W. and Green, D. G. 1965. Monocular versus binocular visual acuity. Nature, London 208, 191--192.Google ScholarCross Ref
- Di Battista, G., Eades, P., Tamassia, R., and Tollis, I. G. 1999. Graph Drawing: Algorithms for the Visualization of Graphs. Prentice-Hall, Englewood Cliffs, NJ. Google ScholarDigital Library
- Frisby, J. P., Buckley, D., and Duke, P. A. 1966. Evidence for recovery of lengths of real objects seen with natural stereo viewing. Perception 25, 129--154.Google ScholarCross Ref
- Fruchterman, T. and Reingold, E. 1991. Graph drawing by force-directed placement, Software Practice and Experience 21, 11, 1129--1164. Google ScholarDigital Library
- Howard, I. P. and Rogers, B. J. 1995. Binocular Vision and Stereopsis. Oxford Psychology Series No 29. Oxford University Press. Oxford.Google Scholar
- Huang, M. L., Eades, P., and Wang, J. 1998. Online animated visualization of huge graphs using a modified spring algorithm. Journal of Visual Languages and Computing 9, 6, 623--645.Google ScholarDigital Library
- Kleiberg, E., van d. Wetering, H., and van Wijk, J. J. 2001. Botanical visualization of huge hierarchies. IEEE Symposium on Information Visualization, San Diego. 87--94. Google ScholarDigital Library
- Munzner, T. 1997. H3: Laying out large directed graphs in 3D hyperbolic space. In Proc. IEEE Symposium on Information Visualization. 2--10. Google ScholarDigital Library
- Munzner, T., Guimbretière, F., and Robertson, G. 1999. Constellation: A visualization tool for linguistic queries for MindNet. In Proc. IEEE Symposium on Information Visualization (Oct.). San Francisco, CA. 132--135. Google ScholarDigital Library
- Norman, J. F., Todd, J. T., Perotti, V. I., and Tittle, J. S. 1996. The visual perception of 3-D length. Journal of Experimental Psychology: Human Perception and Performance 22, 173--186.Google ScholarCross Ref
- Parker, G., Franck, G., and Ware, C. 1998. Visualization of large nested graphs in 3D: Navigation and interaction. Journal of Visual Languages and Computing 9, 299--317.Google ScholarCross Ref
- Plaisant, C., Grosjean, J., and Bederson, B. B. 2002. SpaceTree: Supporting exploration in a large node-link tree, design evolution and empirical evaluation. IEEE Symposium on Information Visualization, Boston, MA. 57--64. Google ScholarDigital Library
- Robertson, G., Mackinlay, J. D., and Card, S. W. 1993. Information visualization using 3D interactive animation. Communications of the ACM 36, 4, 57--71. Google ScholarDigital Library
- Rogers, B. and Cagnello, R. 1989. Disparity curvatures and the perception of three-dimensional surfaces Nature, London 339, 137--139.Google ScholarCross Ref
- Sollenberger, R. L. and Milgram, P. 1993. The effects of stereoscopic and rotational displays in a three-dimensional path-tracing task. Human Factors 35, 3, 483--500.Google ScholarCross Ref
- Tyler, C. 1975. Spatial organization of binocular disparity sensitivity. Vision Research 15, 583--590.Google ScholarCross Ref
- Uumori, K. and Nishida, S. 1994. The dynamics of the visual system in combining conflicting KDE and binocular stereopsis cues. Perception and Psychophysics 55, 5, 526--536.Google ScholarCross Ref
- van Ee, R. and Schor, C. M. 2000. Unconstrained stereoscopic matching of lines. Vision Research 40, 151--162.Google ScholarCross Ref
- Wallach, H. and O'Connell, D. N. 1953. The kinetic depth effect. Journal of Experimental Psychology 45, 205--217.Google ScholarCross Ref
- Ware, C. and Bobrow, R. 2005. Supporting visual queries on medium-sized node-link diagram. Information Visualization 4, 49--58. Google ScholarDigital Library
- Ware, C. and Franck, G. 1996. Evaluating Stereo and motion cues for visualizing information nets in three dimensions. ACM Transactions on Graphics 15, 2, 121--139. Google ScholarDigital Library
- Ware, C., Arthur, K., and Booth, K. S. 1993. Fishtank virtual reality. INTERCHI'93 Proceedings. 37--42. Google ScholarDigital Library
- Wheatstone, C. 1838. Contributions to the physiology of vision. Part the first. On some remarkable and hitherto unobserved phenomena of binocular vision. Philosophical Transactions of the Royal Society 128, 371--394.Google ScholarCross Ref
- Wills, G. J. 1999. NicheWorks: Interactive visualization of very large graphs. Journal of Computational and Graphical Statistics 8, 2, 190--212Google ScholarCross Ref
Index Terms
- Visualizing graphs in three dimensions
Recommendations
Reevaluating stereo and motion cues for visualizing graphs in three dimensions
APGV '05: Proceedings of the 2nd symposium on Applied perception in graphics and visualizationIt has been known for some time that larger graphs can be interpreted if viewed in 3D than in 2D. Both kinetic depth cues and stereoscopic depth cues increase the size of the structure that can be interpreted. However, prior studies were carried out ...
Visualizing Group Structures in Graphs: A Survey
Graph visualizations encode relationships between objects. Abstracting the objects into group structures provides an overview of the data. Groups can be disjoint or overlapping, and might be organized hierarchically. However, the underlying graph still ...
Hierarchical Edge Bundles: Visualization of Adjacency Relations in Hierarchical Data
A compound graph is a frequently encountered type of data set. Relations are given between items, and a hierarchy is defined on the items as well. We present a new method for visualizing such compound graphs. Our approach is based on visually bundling ...
Comments