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Details of Grant 

EPSRC Reference: EP/E02839X/1
Title: ShoePrint Analysis and Recognition (SPAR)
Principal Investigator: Allinson, Professor NM
Other Investigators:
Researcher Co-Investigators:
Dr M Pavlou Dr J Sivarajah
Project Partners:
Foster & Freeman Ltd
Department: Electronic and Electrical Engineering
Organisation: University of Sheffield
Scheme: Standard Research
Starts: 01 December 2006 Ends: 31 May 2010 Value (£): 488,432
EPSRC Research Topic Classifications:
Image & Vision Computing
EPSRC Industrial Sector Classifications:
No relevance to Underpinning Sectors
Related Grants:
Panel History:  
Summary on Grant Application Form
There is no branch of detective science that is so important and so much neglected as the art of tracing footsteps (Sherlock Holmes: A Study in Scarlet)This quote remains almost as true today as it was when Sir Arthur Conan-Doyle penned it in 1887. Changes in Police Powers, which came into force in January 2006, will permit footwear evidence to be treated in the same manner as fingerprint and DNA evidence. Namely, that the Police have the right to acquire impressions of all arrestees' footwear and that they can be held and searched on a National database. Currently the recovery of footwear marks from crime scenes has been patchy across the individual UK Police Forces but it is recognized that there is more chance to recover footwear marks from burgled premises than fingerprint marks. Though footwear evidence is not as unique or as permanent as fingerprints or DNA, it can provide very valuable intelligence and in some cases evidence to courtroom standards. Current practice in identifying shoe model from impressions or marks is through the use of manually annotated reference sets of many 1000s of images of shoe models. Such methods are labour intensive and prone to error as footwear examiners can employ different coding schemes. We intend in this project to develop a full automatic system for the rapid and robust classification of shoe model for use in Police custody suites and to develop tools to assist in the forensic examination of scene marks and provide auditable evidential standards. Our existing feasibility study has demonstrated the ability to develop automatic impression classification systems based on the use of contemporary image feature detectors and robust feature descriptors. Luckily most criminals wear trainers and the complexity of the outsole patterns results in many 1000s of identifiable features. By correlating the feature of some query impression to those derived from images in the reference set, we can obtain a short-list of likely candidate models; more intensive graphical models are then employed to identify the specific model. This project will build upon these concepts for different media formats of footwear impressions and scene marks, refine techniques for very large reference sets, cope with partial and scuffed marks, provide tools to link a suspect's shoes to the matching scene marks, and to work with the Police and other organizations to further the application of this technology into operational practice.
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Further Information:  
Organisation Website: http://www.shef.ac.uk