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Details of Grant 

EPSRC Reference: EP/R030855/1
Title: Seeing the future
Principal Investigator: Marshall, Professor A
Other Investigators:
Moran, Dr R Rushton, Professor SK
Researcher Co-Investigators:
Project Partners:
Department: Computer Science
Organisation: Cardiff University
Scheme: Standard Research - NR1
Starts: 01 April 2018 Ends: 30 September 2019 Value (£): 232,767
EPSRC Research Topic Classifications:
Artificial Intelligence
EPSRC Industrial Sector Classifications:
No relevance to Underpinning Sectors
Related Grants:
Panel History:
Panel DatePanel NameOutcome
31 Oct 2017 Human-like Computing Interviews Announced
Summary on Grant Application Form
Newspapers do not report stories about the sun rising or setting. This because what is expected or unchanging is of little interest, what is newsworthy is the unexpected or changing. In 1961 Horace Barlow, a British vision scientist, hypothesised that the sensory systems of the brain work on the same principle, it devotes little investigation to the expected and reports the unusual. It does this by trying to predict what is going to happen and when it fails it funnels resources at the "prediction errors". This makes intuitive sense, the things in a scene that merit attention are typically those that unpredictable or changing. This idea, "predictive coding" has proven very fruitful and today it underpins much research on how the brain works.



The aim of this project is to translate the idea of predictive coding from the fields of psychology and biology to the design of a computer vision system. The system will try to predict the upcoming camera image. Prediction will be based on the previous images seen (over immediate, intermediate and longer time scales), information about movement of the system through space (from the inertial sensor), and knowledge of how objects and people move. Prediction errors will be flagged.

This is a feasibility study, to determine and demonstrate the benefits of such a system and form a basis for future work.

Our specific objectives are to:



i) Evaluate the technical feasibility of building a predictive vision system.

ii) Assess the projected efficiency and accuracy of a predictive vision system.

iii) Evaluate the effectiveness of a predictive vision system for detecting changes or incongruencies in the scene.

iv) Assess the computational completeness and sufficiency of the predictive coding approach (this result will be fed back to the biology/psychology community).

v) Identify potential partners and explore potential industrial, security or healthcare applications of the technology.

vi) Take appropriate steps to protect intellectual property and then release the data and code to the broad research community.

vii) On successful completion seek follow-on funding (research council and/or industrial) for further work.



The project brings together expertise in computer vision, human vision and computational biology across two partner (GW4; Cardiff and Bristol) universities to work on this innovative and cutting edge work. The system is to be built from a stereo camera, an inertial sensor, and a CPU/GPU. This technology is available in some smartphones today. If the efficiency and accuracy benefits are realized then the technology could be based on a smartphone which opens up a broad range of applications, including in healthcare, security and ubiquitous computing.
Key Findings
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Potential use in non-academic contexts
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Impacts
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Summary
Date Materialised
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Further Information:  
Organisation Website: http://www.cf.ac.uk