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The Boujou special effects software was developed from research carried out at the Department of Engineering Science. It enables sophisticated computer generated imagery (CGI) to be quickly and easily added to `real' film footage, facilitating the visual effects that feature so importantly in films such as Harry Potter and X-Men. The software has become an essential tool used by film-makers, TV advert producers, and video game manufacturers, and for instance played a pivotal role in helping `The Curious Case of Benjamin Button' win the 2009 Oscar for Best Visual Effects. Between 2008 and 2013, sales of Boujou totalled £1.37 million and this software boosted productivity and profitability right across the global digital entertainment industry.
Motion blur is the effect that occurs when objects are filmed at speed. Researchers at Bournemouth University's (BU) National Centre for Computer Animation (NCCA) developed a new approach to more accurately model this effect in 3D image production. This produces aesthetically superior images without any penalty in rendering time. The technique was implemented by Pixar in their own films and in the commercial PRMan software they supply to other animation and effects studios in New Zealand, Canada, the USA and the UK, among others. As well as contributing significantly to Pixar's revenue, the technique improves the viewing experience and has been used on virtually every major feature film produced since 2008. This contributes to the global animation industry worth $207 US billion (2012, R1).
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).
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.
The Geometric Modelling and Pattern Recognition (GMPR) Group at Sheffield Hallam University (SHU) has developed and patented internationally-known line projection technologies for fast 3D scan, reconstruction and recognition. Three types of impact can be identified: (i) through our patents, we have licensed to companies in Europe and the USA; (ii) these technologies are being transferred to Small and Medium-sized Enterprises (SMEs) across Europe, through the European funded MARWIN and ADMOS projects; and (iii) social and cultural impacts are evidenced by the 3D scanning of representative items from the Museums Sheffield Metalwork Collection which have been made publicly available on the web, and through the `Man of Steel' community project where a landmark sculpture will form a gateway to South Yorkshire and the Sheffield City Region.
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.
A biomarker is a measurement or physical sign used as a substitute for a clinically meaningful endpoint that measures directly how a patient feels, functions, or survives. Biomarkers can be used to assess changes induced by a therapy or intervention on a clinically meaningful endpoint.
New quantitative image analysis techniques developed at Imperial College have enabled the computation of imaging biomarkers that are now widely used in clinical trials as well as for healthcare diagnostics. This case study illustrates the resulting key impacts including:
Research at the University of Cambridge Department of Engineering (DoEng) since 1997 created methods for reconstructing a three-dimensional (3D) model of an object from a single two-dimensional photograph. Metail, a company founded in 2008, sponsored further research at the DoEng and commercialised the results in an online fashion retailing application. Metail enables customers to select an item of clothing and see how they would look wearing it from a variety of angles, having entered just one photograph of themselves and a few basic body measurements. Metail attracted over GBP3.5M investment. Its application is used by Shop Direct, Tesco, Warehouse, Zalando and Dafiti. Sales data shows that the Metail application increases the propensity of customers to buy and reduces the proportion of goods returned.
Research undertaken at UEA developed revolutionary algorithms for making pictures look better. These algorithms were subsequently engineered into prize winning desktop and embedded applications, resulting in the creation of the spinout company, Imsense Ltd., in 2006.
In July 2010, Imsense Ltd. was acquired by [text removed for publication] and the Imsense technology has now been incorporated into [text removed for publication] product pipeline.
In the late 1990s, a significant barrier to the adoption of virtual reality software was the expense of manually creating models of real-world scenes. To address this, between 1998 and 2004, the ICARUS software system was developed, which enabled the creation of structured, 3D geometric models from a sequence of images or video. The system also pioneered improved methods of camera tracking. ICARUS was subsequently licensed and developed commercially, and became the foundation for video and film post-production products that are used worldwide in the film (e.g. Universal Pictures, Warner Bros, Paramount Pictures) and television (e.g. BBC) industries, underpinning a company with an annual turnover in excess of £1m.