Opening up the Black Box of Sensor Processing Algorithms through New Visualizations
Abstract
:1. Introduction: Human–Computation–Sensor Systems
2. Cognitive Task Analysis
2.1. Weaknesses of Alert/Investigate Human–Machine Architectures
2.1.1. Corroboration
2.1.2. Brittleness
2.1.3. Low Observability
2.1.4. Poor Mental Models
2.2. CTA of Hyperspectral Imaging as a Sample Human–Computation–Sensor System
3. Making Automation Observable
3.1. The Conceptual Problem
3.2. Similarity Matching in Hyperspectral Analysis
- weak targets—low discriminability between target and background;
- masked targets—a background material hides a target material; and
- confusor targets—a background material that is similar to a target material.
3.3. Example Similarity Computation—Cosine Similarity
3.4. Many-to-Many Mapping
4. Interactive Visualization of Similarity Spaces
4.1. Relating Visualization to Conceptual Model
4.2. The Visualization Similarity Space
4.3. Visualization Dynamics
4.4. Visualization Cases—Clear Signal, No Signal, and Signal with Multiple Plausible Matches
4.5. Separating Signal and Background
4.6. Visual Patterns at Scale
5. Discussion
5.1. An Analogical Representation
5.2. Analogical or Categorical Forms of Representation
Supplementary Materials
Acknowledgments
Author Contributions
Conflicts of Interest
Abbreviations
ISR | Intelligence, Surveillance, and Reconnaissance |
FMV | Full Motion Video |
HSA | Hyperspectral Analysis |
CTA | Cognitive Task Analysis |
SAM | Spectral Angle Mapper |
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Morison, A.M.; Woods, D.D. Opening up the Black Box of Sensor Processing Algorithms through New Visualizations. Informatics 2016, 3, 16. https://doi.org/10.3390/informatics3030016
Morison AM, Woods DD. Opening up the Black Box of Sensor Processing Algorithms through New Visualizations. Informatics. 2016; 3(3):16. https://doi.org/10.3390/informatics3030016
Chicago/Turabian StyleMorison, Alexander M., and David D. Woods. 2016. "Opening up the Black Box of Sensor Processing Algorithms through New Visualizations" Informatics 3, no. 3: 16. https://doi.org/10.3390/informatics3030016