School of Electronic Engineering and Computer Science

Modelling Human Memory for Forensic Facial Sketch Matching

Supervisor: Dr Yi-Zhe Song

Facial sketch recognition is an important law enforcement tool for determining the identity of criminals where only an eyewitness account of the suspect is available. In this situation, a forensic sketch artist renders the face of the suspect by hand or with compositing software based on eyewitness description. The facial sketch is then disseminated in the media, but the crucial capability is to then identify the suspect by matching it against a photo mugshot database. This project investigates whether it is possible to model the human memory's forgetting process for faces, and whether such a model can be used to improve the performance of automated facial forensic sketch matching. Forensic facial sketch recognition is a key capability for law enforcement, but remains an unsolved problem. It is extremely challenging because there are three distinct contributors to the domain gap between forensic sketches and photos: The well studied sketch-photo modality gap, and the less studied gaps due to (i) the forgetting process of the eye-witness and (ii) their inability to elucidate their memory. The PhD student will have access to a database of 800 forensic sketches created at different time-delays, which is the largest such dataset to date.