On Matching Skulls to Digital Face Images: A Preliminary Approach

TL;DR

This paper introduces the first skull-face image database and a preliminary semi-supervised transform learning method to match skulls with digital face images, aiming to aid forensic identification.

Contribution

It presents a novel skull-face image database and a preliminary matching approach, addressing the lack of data and methods in this challenging forensic biometrics problem.

Findings

The database enables new research in skull-face matching.

Preliminary results highlight the difficulty of the problem.

Comparison shows existing algorithms are not yet effective.

Abstract

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.