Abstract
When perpetrators wear masks to hide their facial features and avoid being recognized, it poses a significant challenge for law enforcement because the occlusion of facial features impairs recognition. This thesis investigates how contextual congruency and feature-based processing can enhance recognition performance under such conditions, providing valuable insights for improving identification accuracy in real-world settings, particularly when individuals wear masks or only limited facial information is available.
| Original language | English |
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| Qualification | Doctor of Philosophy |
| Awarding Institution |
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| Supervisors/Advisors |
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| Award date | 30 Jun 2025 |
| Place of Publication | Maastricht |
| Publisher | |
| Print ISBNs | 9789465106953 |
| DOIs | |
| Publication status | Published - 30 Jun 2025 |
Keywords
- Masked face matching
- masked face recognition
- congruency effect
- facial processing
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