EPSRC Reference: |
EP/H018557/1 |
Title: |
EPSRC Network on Vision and Language (V&L Net) |
Principal Investigator: |
Belz, Professor A |
Other Investigators: |
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Researcher Co-Investigators: |
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Project Partners: |
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Department: |
Sch of Computing, Engineering & Maths |
Organisation: |
University of Brighton |
Scheme: |
Network |
Starts: |
01 March 2010 |
Ends: |
31 October 2013 |
Value (£): |
104,261
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EPSRC Research Topic Classifications: |
Human Communication in ICT |
Image & Vision Computing |
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EPSRC Industrial Sector Classifications: |
No relevance to Underpinning Sectors |
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Related Grants: |
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Panel History: |
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Summary on Grant Application Form |
The amount of digital information accessible on the web and, more generally, in data repositories of various sorts isgrowing at an ever faster pace. Increasingly, digital information means visual content (image and video), and thisdevelopment has resulted in a situation where computational solutions are lagging behind a diverse range ofcurrent image/video search, processing and management needs. There is a big, and as yet unbridged, semanticgap between visual content and language. Finding solutions for image/video retrieval, automatic image/videoannotation and similar challenges will require this gap to be bridged, and this in turn will require expertise from boththe computer vision (CV) and natural language processing (NLP) fields. Yet, while language and vision are the twoprimary modalities for human perception and computer-mediated communication, the two corresponding computingscience disciplines hardly talk to each other, and this is part of the reason why the language-vision gap is still sowide: NLP research is perhaps not aware enough of the range of possible applications involving visual content andtheir specific language processing requirements; CV can tend to underestimate the complexity of thelanguage processing problem, and currently uses mostly basic language processing technology, whereassophisticated, high-performance tools exist.We propose an EPSRC Network on Vision and Language, V&L Net, to create a forum for researchers from CVand NLP to meet and exchange ideas, expertise and technology. The UK has some of the world's leadingresearchers in NLP and CV. V&L Net aims to tap this body of expertise to create new strategic partnerships aimed atnarrowing the language-vision gap by developing the theory required for solutions to the difficult challenges posedby our increasingly multi-modal world. A successful network will place the UK at the forefront of developing solutionsat the language-vision intersection which have clear commercial potential.Our overarching goal in V&L Net is the creation of a new interdisciplinary research community working towardscomputational solutions for challenges that involve both language and vision. By (i) bringing researchers from thetwo currently separate disciplines of computer vision and language processing together, (ii) facilitating access torelevant information, expertise, and resources, and (iii) stimulating research and pump-priming individual researchprojects, we aim to engender a substantial increase in interdisciplinary research activity. Through this increase inwork bringing to bear expertise from both computer vision and language processing, we expect to see a stepchange in progress towards solutions for a range of real-world challenges as well as theoretical questions. Whilethe latter will tend to have a more long-term impact (laying the groundwork for future breakthroughs), the formerhave substantial potential to result in ground-breaking new products and services that will improve people's qualityof life in diverse ways even in the short to medium term. People with impairments in sight, hearing and cognitive ability will benefit from assistive technology that will help them access multiple modalities. Improvements in image search and retrieval will enhance online search experience, as well as help institutions such as hospitals and police forces to cope with the massive amounts of images and videos they deal with daily.
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Key Findings |
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Potential use in non-academic contexts |
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Impacts |
Description |
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Summary |
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Date Materialised |
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Sectors submitted by the Researcher |
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Project URL: |
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Further Information: |
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Organisation Website: |
http://www.bton.ac.uk |