Similar case studies

REF impact found 14 Case Studies

Currently displayed text from case study:

Automated Personal Identity Recognition Using Face Detection: Spin Out OmniPerception

Summary of the impact

Research in biometrics carried out at Surrey since 1995 has generated IP relating to a number of aspects of automatic face recognition, which resulted in significant performance improvement, rendering this biometric technology commercially exploitable.

The advances made at Surrey include illumination invariant imaging, face detection/localisation using robust correlation, innovative face skin texture representation using a multiscale local binary pattern descriptor, a patented (and exceptionally compact) person specific discriminant analysis, facial component based matching, and patented multi-algorithmic fusion.

Through an IP agreement, these innovations have been commercially exploited by the University spinout company OmniPerception, which has developed products for various security applications.

Submitting Institution

University of Surrey

Unit of Assessment

Electrical and Electronic Engineering, Metallurgy and Materials

Summary Impact Type

Technological

Research Subject Area(s)

Information and Computing Sciences: Artificial Intelligence and Image Processing, Computation Theory and Mathematics, Information Systems

EFIT-V Facial Recognition Software

Summary of the impact

Research conducted within the School of Physical Sciences (SPS) at the University of Kent has led to the development and successful commercialisation of facial identification software named EFIT-V. First sold in 2007, this software is now used by more than 70 police forces internationally and has revolutionized the way eyewitnesses and victims of crime create computerised facial likenesses of offenders. These images are circulated to police intelligence units, and the general public, leading to the identification and arrests of offenders. Police Identification rates have jumped from 5% to 55% as a result of this software. With a current annual turnover exceeding £250K, which is projected to reach £600K by 2015, Kent spinout company Visionmetric has made significant impact with EFIT-V, and achieved a position of commercial dominance in the UK, and around the world.

An offender in police custody recognised and identified using Kent’s EFIT-V technology
    (Image courtesy of Merseyside Police 2012)
An offender in police custody recognised and identified using Kent’s EFIT-V technology
(Image courtesy of Merseyside Police 2012)

Submitting Institution

University of Kent

Unit of Assessment

Physics

Summary Impact Type

Technological

Research Subject Area(s)

Information and Computing Sciences: Artificial Intelligence and Image Processing
Medical and Health Sciences: Neurosciences
Psychology and Cognitive Sciences: Psychology

Walk This Way: Leading the World in Gait Biometrics

Summary of the impact

Gait recognition research has produced impacts on public policy, on national security processes, on forensic service practice, on culture and society. The notion that people can be recognised by the way they walk was invented as a totally new means to identify people and has gained increasing popularity, reflected by its inclusion in an episode of BBC premier series Spooks. This followed considerable scientific development after its invention at Southampton in 1994, culminating in impacts that include its integration in a commercial system piloted by the National Physics Laboratory, novel forensic use in a criminal conviction, its take up by researchers at the Serious Organised Crime Agency and its focus by The Forensic Science Society. Southampton has retained its position at the forefront of gait biometrics research, collaborating nationally and internationally and driving prolific media engagement that has furthered this new technology and increased its global impact

Submitting Institution

University of Southampton

Unit of Assessment

Electrical and Electronic Engineering, Metallurgy and Materials

Summary Impact Type

Technological

Research Subject Area(s)

Information and Computing Sciences: Artificial Intelligence and Image Processing

Classification within forensic datasets

Summary of the impact

This Keele University research into advanced signal processing and classification methods has led to novel algorithms capable of isolating subtle patterns in complex data. This has been applied in two highly significant application areas: first to the problem of image source identification and second to the problem of unobtrusive but highly secure authentication methods. In the first case this has enabled images captured by mobile phone cameras to be reliably and evidentially linked to source devices. This has huge applicability to those fighting terrorism, paedophile rings and civil unrest by extending detection capabilities to mobile phones in an era in which they are rapidly replacing dedicated cameras. It helps to prove, for example, that a photograph entered as evidence was captured by a specific mobile phone. As most phones can be tied to their user or owner this is extremely important to the successful detection and prosecution of offenders.

In the second case it has enabled criminal record checks to be carried out securely online where previous paper-based systems were both too slow for purpose (taking weeks or months) and inherently insecure, leaving key posts unfilled in the health care industries and education sector; so benefitting the public by solving a problem that was having a negative impact on the running of these public services.

Submitting Institution

Keele University

Unit of Assessment

Computer Science and Informatics

Summary Impact Type

Technological

Research Subject Area(s)

Information and Computing Sciences: Artificial Intelligence and Image Processing
Engineering: Electrical and Electronic Engineering

Synergistic impacts from cross-sectoral research in signal and image processing technology for aerospace non-destructive evaluation and medical non-invasive diagnosis

Summary of the impact

A unique aspect of the signal and image processing research at the University of Central Lancashire (UCLan) lies in exploitation of the synergies between non-destructive evaluation (NDE) of aerostructures in the aerospace manufacturing sector and non-invasive diagnosis (NID) of patients in the medical sector. For the former, through collaborative research with world leading aerospace companies, data processing technologies used in medical NID have been exploited to ensure structural safety of aircraft at reduced time and cost. For the latter, through collaborative research with the UCLan led Europe-wide network which includes top medical research centres and hospitals, sensing technologies used in aerospace NDE have been exploited to create new measurement modalities for quantitative medical diagnosis of major diseases. Furthermore, arising out the cross-sectoral and interdisciplinary research the Tele-immersive Digital Manufacturing facility (TiM) emerges as our vision for the factory of the future which has attracted investments from the world leading digital technology providers and made impacts on one of the most important manufacturing regions in the world.

Submitting Institution

University of Central Lancashire

Unit of Assessment

General Engineering

Summary Impact Type

Technological

Research Subject Area(s)

Mathematical Sciences: Statistics
Information and Computing Sciences: Artificial Intelligence and Image Processing
Engineering: Electrical and Electronic Engineering

EvoFIT: Applying Psychology To The Identification Of Criminals

Summary of the impact

Our research has made an outstanding contribution to the ability of police forces to apprehend criminal suspects, particularly in cases of serious violent crime. EvoFIT is a facial composite system (software and procedures), designed to help victims and witnesses of crime to create a likeness of the perpetrator's face. It was conceived by Professor Peter Hancock in the mid-1990s and has been developed into an effective system that is in use by police forces across the UK and abroad. Forces using EvoFIT have actively collaborated with assessment of the system, and evidence from field trials clearly demonstrates the impact: a world-leading 25-60% of composites made with EvoFIT directly lead to an arrest, four times better than the best previous system used by police forces. Our novel methods for interviewing witnesses and for presentation of composites have enhanced the success of EvoFIT, and are now incorporated in competitor composite systems used by other police forces.

Submitting Institution

University of Stirling

Unit of Assessment

Psychology, Psychiatry and Neuroscience

Summary Impact Type

Legal

Research Subject Area(s)

Psychology and Cognitive Sciences: Psychology

Craniofacial Depiction for Forensic Identification and Archaeological Investigation

Summary of the impact

Wilkinson has developed, evaluated and applied techniques, standards and datasets for facial depiction and identification of the dead. The impacts include:

  • Improved social welfare by establishing an international forensic tool that has enhanced forensic identification from human remains, and correspondingly improved law enforcement services and disaster victim identification.
  • Delivered highly skilled people and international standards in forensic craniofacial identification.
  • Provided cultural enrichment through enhanced public engagement with science and art internationally, through the craniofacial depiction of historical figures and ancient human remains.

Submitting Institution

University of Dundee

Unit of Assessment

Art and Design: History, Practice and Theory

Summary Impact Type

Technological

Research Subject Area(s)

Biological Sciences: Genetics
Information and Computing Sciences: Artificial Intelligence and Image Processing
Studies In Human Society: Anthropology

3: Improvements to the Performance and Management of Mass Transit Systems in Major Cities

Summary of the impact

Methods have been developed to characterise and evaluate the performance of mass transit systems which have then been applied in 60 of the world's major cities. The financial benefit, as quantified by mass transit operators, is in excess of £0.5 Billion between 2003 and 2013. Examples of impact include cost savings for escalator renewal by London Underground (2009-ongoing), influencing fares policy in Hong Kong (2003, 2012) and the adoption of performance measurement systems, developed by Imperial, by Chinese metros (2010-ongoing). This impact has been enabled by the creation and subsequent facilitation of 5 global consortia comprising over 70 metro, suburban rail and urban bus operators.

Submitting Institution

Imperial College London

Unit of Assessment

Civil and Construction Engineering

Summary Impact Type

Economic

Research Subject Area(s)

Information and Computing Sciences: Artificial Intelligence and Image Processing, Information Systems
Commerce, Management, Tourism and Services: Transportation and Freight Services

User Authentication Methodologies for Secure and Competitive Business

Summary of the impact

Between 2003-2008 our research into an efficient multifactor-multimodal biometric authentication method for smartcards enabled Ecebs (http://www.ecebs.com/), a small-to-medium enterprise company specialising in smartcard software solutions to increase their patent portfolio, widen its product and service offering, improve their competitive position and create new business opportunities. In 2007 Ecebs was acquired by Trainline Investment Holdings Ltd (today known as The Trainline.com), and subsequently in 2012 by Bell ID, a global provider of smartcard/contactless/mobile solutions.

Submitting Institution

Glasgow Caledonian University

Unit of Assessment

Computer Science and Informatics

Summary Impact Type

Technological

Research Subject Area(s)

Information and Computing Sciences: Artificial Intelligence and Image Processing, Data Format

20 - Smart Software for Autonmous Maritime Systems

Summary of the impact

Strong collaboration and associated technology transfer from ERPE have enabled SeeByte to stay at the forefront of technology, securing strategic partnerships including Subsea7, BAE SYSTEMS and the US Navy in the offshore and military markets. This has enabled sustained employment in the science and engineering sector growing to 50 staff and financial growth, 15 technology licenses from ERPE have directly or indirectly generated £11 million in revenues for SeeByte in the REF impact period. In October 2013 SeeByte was acquired by Bluefin Robotics Inc, a spin out of MIT owned by the Battelle group [text removed for publication].

Submitting Institutions

Heriot-Watt University,University of Edinburgh

Unit of Assessment

General Engineering

Summary Impact Type

Technological

Research Subject Area(s)

Information and Computing Sciences: Artificial Intelligence and Image Processing, Information Systems
Engineering: Electrical and Electronic Engineering

Filter Impact Case Studies

Download Impact Case Studies