Face recognition has received significant attention because of its numerous applications in
access control, law enforcement, security, surveillance, Internet communication and …

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 …

Heterogeneous face recognition (HFR) aims at matching facial images acquired from
different sensing modalities with mission-critical applications in forensics, security and …

In recent years, heterogeneous face biometrics has attracted more attentions in the face
recognition community. After published in 2009, the HFB database [7] has been applied by …

Cross-modality face recognition is an emerging topic due to the wide-spread usage of
different sensors in day-to-day life applications. The development of face recognition …

Local feature descriptor is an important module for face recognition and those like Gabor
and local binary patterns (LBP) have proven effective face descriptors. Traditionally, the form …

Heterogeneous face recognition (HFR) involves matching two face images from alternate
imaging modalities, such as an infrared image to a photograph or a sketch to a photograph …

The problem of matching a forensic sketch to a gallery of mug shot images is addressed in
this paper. Previous research in sketch matching only offered solutions to matching highly …

Visual versus near infrared (VIS-NIR) face recognition is still a challenging heterogeneous
task due to large appearance difference between VIS and NIR modalities. This paper …

Surveillance cameras today often capture NIR (near infrared) images in low-light
environments. However, most face datasets accessible for training and verification are only …