We present a first effort to evaluate the possible utility of a new type of surface glyphs intended for visualizations of multivariate spatial data. The glyphs are based on results from vision research suggesting that our perception of metric 3D structure is distorted and imprecise relative to the actual scene before us; only a class of qualitative properties of the scene is perceived with accuracy. These properties are best characterized as being invariant over affine but not Euclidean transformations. A large number of possible 3D glyphs for the visualization of spatial data can be constructed using such properties. One group of such glyphs is based on the local sign of surface curvature. We investigated this group in two visualization experiments. The results show that available sources of 3D structural information were sufficient for our subjects to make fast and accurate judgments. Some implications for visualization are also discussed.
ChernoffH.Using faces to represent points in k-dimensional space. Journal of the American Statistical Association1973; 68: 361–368.
2.
PicketRMGrinsteinGG. Iconographic displays for visualizing multidimensional data. IEEE Conference on Systems, Man and Cybernetics 1988 (Beijing and Shenyang, China); IEEE Computer Society Press: Chicago, 1988; 1: 514–519.
3.
ChambersJMClevelandWSKleinerBTukeyPA. Graphical Methods for Data Analysis. Wadsworth: Belmont, CA, 1983; 395pp.
4.
MezzichJEWorthingtonDRL. A comparison of graphical representations of multidimensional psychiatric diagnostic data. In: WangP (Ed). Graphical Representation of Multivariate Data. Academic Press: New York, 1978; 123–141.
5.
PaznerMRipleyN.Interactive multivariate pattern images. GeoTec Event–GIS 2002 Conference (Toronto, ON); Proceedings published on CD ROM by GEOTec Media: Boulder, CO, 2002; 6pp.
6.
ZhangXPaznerM.The imagemap technique for multivariate geospatial data visualization: Approach and software system. Cartography and Geographic Information Science2004; 31: 29–41.
7.
LindMBinghamGPForsellC.Metric 3D structure in visualizations. Information Visualization2003; 2: 51–57.
8.
ToddJTNormanJF. The visual perception of 3-D shape from multiple cues: Are observers capable of perceiving metric structure?. Perception & Psychophysics2003; 65: 31–47.
9.
ToddJTTittleJSNormanJF. Distortions of three-dimensional space in the perceptual analysis of motion and stereo. Perception1995; 24: 75–86.
10.
ToddJT. The visual perception of 3D shape. Trends in Cognitive Science2004; 8: 115–121.
11.
TittleJSWoodsDWHowardMPhillipsF.The role of 2-D and 3-D task performance in the design of and use of visual displays. 45th Annual Meeting of the Human Factors and Ergonomics Society 2001 (Minneapolis, MN), Human Factors and Ergonomics Society: Santa Monica, CA, 2001; 1215–1219.
12.
MackinlayJD. Automating the design of graphical presentations of relational information. In: CardSKMackinlayJDSchneidermanB (Eds). Information Visualization: Using Vision to Think. Morgan Kaufmann Publishers: San Francisco, CA, 1999; 66–81.
13.
WareC.Information Visualization: Perception for Design. Morgan Kaufmann Publishers: San Francisco, CA, 2000; 438pp.
LindMForsellCAllardA.Effective visualizations for large displays–the role of transsaccadic memory. Third IASTED International Conference on Visualization, Imaging, and Image Processing 2003 (VIIP′03) (Benalmadena, Spain), Zurich; Switzerland, 1028–1033.
16.
CaelliTBevanP.Probing the spatial frequency spectrum for orientation sensitivity in stochastic textures. Vision Research1983; 23: 39–45.
17.
LightnerNJ. Model testing of users' comprehension in graphical animation: The effect of speed and focus areas. International Journal of Human-Computer Interaction2001; 13: 53–73.
18.
HochbergJ.Perception as purposeful inquiry. Behavior and Brain Sciences1999; 22: 619–620.
19.
IrwinDE. Eye movements and perception. In: SmelserNJBaltesPB (Eds). International Encyclopedia of the Social & Behavioral Sciences. Elsevier Science: 2001; 9: 5208–5210.
20.
LunneborgCE. Data Analysis by Resampling: Concepts and Applications. Duxbury: Pacific Grove, CA, 2000; 550pp.
21.
FredengrenX.Symmetrical polygons as symbols for computer generated visualization. Unpublished master thesis, Uppsala University, Uppsala, Sweden, 2003.
22.
GarnerWR. The Processing of Information and Structure. Lawrence Erlbaum Associates: Hillsdale, New York, NJ, 1974. 203pp.
23.
WitkinAKassM.Reaction diffusion textures. Eight Annual Conference on Computer Graphics and Interactive Techniques SIGGRAPH′91 (Las Vegas, NV), ACM Press: New York, 1991; 35: 299–308.
24.
LoweDG. Perceptual Organization and Visual recognition. Unpublished doctoral dissertation, Stanford University: Stanford, CA, 1984.
25.
BiedermanI.Recognition-by-components–a theory of image understanding. Psychological Review1987; 94: 115–147.
