2014/09/17 by Ouyang, Shuxin, Hospedales, Timothy, Song, Yi-Zhe +1
#A.1 #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #I.4.9 #I.5.4
paper · doi:10.48550/arxiv.1409.5114
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.