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Research at the University of Cambridge Department of Engineering on computer vision tracking led to the creation of Extra Reality Limited in 2010, which was subsequently acquired by a new company called Zappar Limited in May 2011. Zappar employs 17 staff and had revenue of GBP612k in the financial year 2012/13, an increase of 35% on the previous year.
Over 50 different brands have used Zappar's augmented reality application across more than 300 offerings in over 17 countries to deliver entertainment-based marketing interactions from 2011 to 2013. [text removed for publication] Examples of partners include Disney, Warner Brothers and Marvel. Zappar has changed attitudes in the media sector by showing that "augmented reality is finally ready for prime time" (President, Creative Strategies Inc, Time Online, 2012).
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
Many of the top supercomputers use Graphical Processing Units (GPUs) to accelerate scientific computing applications with less energy consumption and lower overall cost. GPUs achieve this by having comparatively large numbers of simple processing elements when compared against CPUs, which have fewer, more sophisticated, elements. However, to take full advantage of GPUs requires quite different algorithms and implementation techniques for mathematical software libraries. Researchers at the University of Oxford have developed a number of such algorithms and implementation techniques over the period 2008-2013, which have been incorporated into software libraries distributed by NAG, NVIDIA and the Apache Foundation and have enhanced the performance up to 150x compared with single thread CPU calculations and 20x relative to multithreaded CPU calculations. These libraries are used by large numbers of application developers worldwide.
Our impact on the theory and practice of biometrics (identification of individuals through measurement/analysis of their physiological/behavioural characteristics) embraces contributions to technological development, to general systems-level principles and to public policy and professionalisation issues. Our research and consequent engagement across the stakeholder community has impacted on the technological development of practical biometrics through take-up by industry (e.g. InMezzo, one of the UK's leading secure information specialists, has enhanced identity authentication procedures), company spinout (the EFIT-V facial recognition suite from VisionMetric Ltd fundamentally changed the means by which facial composites are created and is now used by more than 85% of Britain's Police Forces), leadership of the development of standards for the expanding commercial marketplace (e.g. establishment of standards for image acquisition for e-passports and other access control applications) and policy-level input to Government and International Professional Bodies, providing long-term support for practical deployment and end- user engagement (the Biometrics Assurance Group with Fairhurst as an independent member reported the security risk and problems identifying fingerprints within the UK government's £5.6bn ID card scheme proposal).
In response to the deficiencies in bank risk management revealed following the 2008 financial crisis, one of the mandated requirements under the Basel III regulatory framework is for banks to backtest the internal models they use to price their assets and to calculate how much capital they require should a counterparty default. Qiwei Yao worked with the Quantitative Analyst — Exposure team at Barclays Bank, which is responsible for constructing the Barclays Counterpart Credit Risk (CCR) backtesting methodology. They made use of several statistical methods from Yao's research to construct the newly developed backtesting methodology which is now in operation at Barclays Bank. This puts the CCR assessment and management at Barclays in line with the Basel III regulatory capital framework.
In a series of papers published from 1999 on, Aitken (Maxwell Institute) and collaborators applied Bayesian statistics to develop a methodology for the quantification of judicial evidence derived from forensic analyses. They proposed and implemented procedures for (i) determining the optimal size of samples that should be taken from potentially incriminating material (such as drugs seized); and (ii) the estimation of likelihood ratios characterising evidence provided by multivariate hierarchical data (such as the chemical composition of crime-scene samples). Their procedures have been recommended in international guideline documents (including a 2009 publication by the United Nations Office on Drugs and Crime) and have been routinely used by forensic science laboratories worldwide since 2008. The research has therefore had an impact on the administration of justice, leading to a better use of evidence and accompanying judicial and economic benefits. Examples are given from laboratories in Australia, Sweden and The Netherlands.
Professor Kautz and his team have developed two photo manipulation and processing methods (Exposure Fusion and local Laplacian filtering) that are used to produce well-exposed photographs with tuneable local contrast. Both are robust and consistent without requiring any per-image parameter tuning. Due to its reliability and effectiveness, Exposure Fusion is now considered the standard method for blending multiple photographs into a single well-exposed photograph, and is used by a large number of commercial and non-commercial products. Local Laplacian filtering was chosen by Adobe Systems Incorporated to be the default tool for image enhancements in Adobe Lightroom and Adobe Camera Raw. As a result, these methods are now in the hands of hundreds of thousands users, who use them to create and manipulate well-exposed digital photographs.
Research at Kingston University into methods for tracking pedestrians and monitoring crowds using computer vision techniques has been translated into commercial products by Ipsotek Ltd and BAe Systems, resulting in economic benefits to these companies from sales of these products.
These products have been sold to high-profile customers including the London Eye, the O2 Arena and the Australian Government, providing significant commercial benefits, employment and growth for both companies, as well as providing an economic impact for these customers.
The International HapMap project was a major international research collaboration to map the structure of common human genetic variation across populations from Europe, Asia and Africa. Mathematical Scientists from the University of Oxford played key roles in the development of statistical methods for the project, along with its overall design and management of the International HapMap Project.
Companies have used HapMap as the primary resource to design genome-wide microarrays to make novel discoveries in, for example, pharmacogenetic studies. The size of this market is estimated at $1.25 billion.
One novel discovery has led to a genetic test that is predictive of sustained viral suppression in patients treated for chronic hepatitis C. An estimated 2.7 to 3.9 million people are affected by HCV infection. This test is sold commercially by the company LabCorp and is a significant contributor to the company's testing volume. Finally, the project has been important in widening the public understanding of genetic variation.
Phase unwrapping is an essential algorithmic step in any measurement system or sensor that seeks to determine continuous phase. Instances of such devices are widespread: e.g. image reconstruction in magnetic resonance imaging (MRI), synthetic aperture radar (SAR) by satellite systems, analysis of seismic data in geophysics and optical instrumentation, to name but a few. Without successfully solving the phase unwrapping problem these instruments cannot function.
The topic is well developed and competition among algorithms is fierce. In 2012 alone, some 235 papers, most of which were describing potential new algorithms, were published in the area. But the continuing need for high-speed, automated and robust unwrapping algorithms poses a major limitation on the employability of phase measuring systems.
Working originally within the context of structured light 3D measurement systems, our research has developed new phase image unwrapping algorithms that constitute significance advances in speed, automation and robustness. The work has led to adoption by industry, as well as use in commercial and government research centres around the globe. Our approach since 2010 has been to make these algorithms freely available to end users. Third parties have gone on to translate our algorithms into other languages, widely used numerical software libraries have incorporated the algorithms and there are high profile industrial users.