Abstract
Heterogeneous face recognition (HFR) refers to matching face imagery across different domains. It has received much interest from the research community as a result of its profound implications in law enforcement. A wide variety of new invariant features, cross-modality matching models and heterogeneous datasets are being established in recent years. This survey provides a comprehensive review of established techniques and recent developments in HFR. Moreover, we offer a detailed account of datasets and benchmarks commonly used for evaluation. We finish by assessing the state of the field and discussing promising directions for future research.
| Original language | English |
|---|---|
| Pages (from-to) | 28-48 |
| Number of pages | 21 |
| Journal | Image and vision computing |
| Volume | 56 |
| Early online date | 26 Sept 2016 |
| DOIs | |
| Publication status | Published - Dec 2016 |
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