A Survey on Heterogeneous Face Recognition: Sketch, Infra-red, 3D and Low-resolution
This is an incremental survey paper that provides a comprehensive overview for researchers and practitioners in law enforcement and related areas.
The paper surveys heterogeneous face recognition (HFR), which tackles the problem of matching face images across different domains like sketches and infrared, and reviews established techniques, recent developments, datasets, and benchmarks in the field.
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 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.