Interactive Pattern Discovery with Mirage
A fundamental concern in data analysis is to
find correlations among different things.
Mirage uses exploratory visualization,
intuitive graphical operations to help
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Track horizontal correlations across
different types of attributes for the same
objects or events
•
Track vertical correlations across layers of
abstraction from signals to the results of
analysis
•
Integrate human and machine pattern
recognition capabilities
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Vertical Correlations across Layers of Analysis
Raw Images
Processed Images
Numerical Features
Classes and Groups
Validation in Input Domain
Relationship between Groups
Interpretation in Context
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Horizontal Correlations:
Similarity of Objects from Different Perspectives
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Objects can be described by many types of attributes:
position, morphology, color, spectra, temporal variability, motion parameters …
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Meaningful similarity metric exists only for attributes of the same type
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Similar groups found from one perspective need to be correlated to those
from others
e.g. Are the objects similar in color also similar in shape?
Shape groups
Color groups
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Human / Machine Interaction in Pattern Discovery
Domain expertise
Hypotheses from theory or intuition
Decisions in algorithmic choices
Interpretation in context
Visualized data geometry
Systematic exploration control
Computed features & data structures
Tentative classifications, indicators
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