On Matching Skulls to Digital Face Images: A Preliminary Approach
This addresses a critical forensic need for law enforcement to identify human skulls, though it is an incremental step as it provides foundational data and a basic method.
The paper tackles the problem of automatically matching skulls to digital face images for forensic identification, introducing the first public database (IdentifyMe) and a preliminary semi-supervised transform learning approach, with experimental results highlighting the challenge but lacking concrete performance numbers.
Forensic application of automatically matching skull with face images is an important research area linking biometrics with practical applications in forensics. It is an opportunity for biometrics and face recognition researchers to help the law enforcement and forensic experts in giving an identity to unidentified human skulls. It is an extremely challenging problem which is further exacerbated due to lack of any publicly available database related to this problem. This is the first research in this direction with a two-fold contribution: (i) introducing the first of its kind skull-face image pair database, IdentifyMe, and (ii) presenting a preliminary approach using the proposed semi-supervised formulation of transform learning. The experimental results and comparison with existing algorithms showcase the challenging nature of the problem. We assert that the availability of the database will inspire researchers to build sophisticated skull-to-face matching algorithms.