Icon based visualization techniques

1. ICON BASED VISUALIZATION
TECHNIQUES
PRESENTED BY:
WAFA QAISER KHAN

2. ICON BASED VISUALIZATION TECHNIQUES
 Uses small icons to represent multidimensional
data values.
TWO POPULAR ICON-BASED TECHNIQUES
1. Chernoff faces
2. Stick figures

3. General Techniques:
 Shape coding: Use shape to represent
certain information encoding.

4.  Color icons: Use color icons to encode
more information.
 Tile bars: Use small icons to represent
the relevant feature vectors in document.

5. CHERNOFF FACES
• Introduced in 1973 by statistician Herman
Chernoff.
• They display multidimensional data
of up to 18 variables (or dimensions) as a
cartoon human face.
• Chernoff faces help reveal trends in the data.

6. • A way to display variables on a two-dimensional
surface. For instance, let x be eyebrow slant, y be
eye size, z be nose length, etc. The above figures
show faces produced using 10 characteristics--
head eccentricity, eye size, eye spacing, eye
eccentricity, pupil size, eyebrow slant, nose size,
mouth shape, mouth size, and mouth opening.

7.  Viewing large data can be tedious.
 Chernoff faces make the data easier for users to
digest.

9. STICK FIGURE
 This technique maps multidimensional data to
five-piece stick figure.
 Each figure has four limbs and a body.
 Two dimensions are mapped to the display (x
and y) axes and the remaining dimensions are
mapped to the angle or length of the limbs.

12.  Figure shows census:
 Age and income are mapped to the display axes.
 Remaining dimensions gender, education and so on are
mapped to stick figures.
 Stick figures having a similar shape, means that they
are similar with respect to the dimensions that are
assigned to the limbs of the stick figure icon.
 The resulting visualization shows texture
patterns, reflecting data trends.

13. CONCLUSION
 Chernoff faces help reveal trends
in the data and are easy to understand.
 Stick figures maps multidimensional data to
five-piece stick figure.

14. THANKYOU