Teaching:TUW - UE InfoVis WS 2008/09 - Gruppe 03 - Aufgabe 1 - Chernoff Face
Introduction
According to wikipedia a Chernoff face represents multivariate data in form of a face [Wikipedia, 2008]. So instead of looking at a bunch of different numbers in a vector a human can look on faces, where each face describes a data set which can contain up to 18 dimensions.
Also the slightest change of the vector results in a different face. Studying faces the whole life-time the human brain is more used to distinguish between faces than vectors. Chernoff faces therefore are often used in statistic presentations like in Dr. Eugen Turners Map “Life in Los Angeles”.[Turner, 1977]
File:LifeInLosAngeles.jpg [Turner, 1977]
Faces are type of glyph, a graphical object whose properties represent data values
The idea of displaying faces to represent multivariate data was first published in 1973 in The Journal of American National Statistic by Herman Chernoff who was born in 1923 in America. Article: “The Use of Faces to Represent Points in K-Dimensional Space Graphically”. [Chernoff, 1973]
The idea in detail
As already said Chernoff faces are simplified faces that can help viewers to detect patterns, groupings, and correlation. Having data sets each dimension is assigned to a facial characteristic. Facial characteristics are for example eybrow slant, eye spacing, head eccentricity, pupil size, and so on. Inside the data set each dimension represents a feature which can be classified. If we say for example that one feature of our face displays the rate of unemployment (rou) we could classify that rate into three classes e.g. rou < 3%, 3%< rou <6% or rou > 6%. So we have three classes for the feature rate of unemployment. As each feature describes a characteristic of a face we could say that the shape of the mouth could stand for the rate of unemployment as figure 2 demonstrates.
Hence, every face unambiguously describes one feature vector, which in turn combines several features to describe one condition, like the quality of life as in [Spinelli and Zhou].
Critics
Chernoff faces may be not that effective it seems. Certain features like the perception of eye size, eyebrow slant and the combination of those both are more influencing for longer viewing times than others. Therefore [Morris et. al, 2000] came to the conclusion that the use of Chernoff faces "may not have a significant advantage over other iconic visualization techniques for multidimensional information visualization.”
References
- [ExampleAuthor et al., 2008] Firstname Lastname. Title of article. Title of Journal (in italic), Volume, number, Date of issue. Help Help:Citation_&_Bibilography_Format
- [Wikipedia, 2008] TODO bla
- [Chernoff, 1973] Herman Chernoff. The Use of Faces to Represent Points in k-Dimensional Space Graphically, Journal of the American Statistical Association, 68 (#342): 361-368, 1973. http://www.jstor.org/pss/2284077
- [Spinelli and Zhou] TODO "Mapping Quality of Life with Chernoff Faces", Joseph G. Spinelli and Yu Zhou, http://gis.esri.com/library/userconf/educ04/papers/pap5000.pdf
- [Turner, 1977] Eugene Turner, Life in LA, 1977 Retrieved at November 7, 2008. http://www.csun.edu/%7Ehfgeg005/eturner/gallery/
- [Morris et al., 2000] Christopher J. Morris, David S. Ebert, Penny Rheingans. An Experimental Analysis of the Effectiveness of Features in Chernoff Faces. 28th AIPR Workshop: 3D Visualization for Data Exploration and Decision Making, Proceedings of SPIE, pages 12- 17, 2000. http://www.csee.umbc.edu/~ebert/papers/Chernoff_990402.PDF