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Details of Grant 

EPSRC Reference: GR/M52793/01
Title: A REAL-TIME IMPLEMENTATION OF AN AID FOR LOW VISION
Principal Investigator: Thomas, Professor B
Other Investigators:
Troscianko, Professor T Easty, Professor D
Researcher Co-Investigators:
Project Partners:
Pre Nexus Migration
Department: Computer Science
Organisation: University of Bristol
Scheme: Standard Research (Pre-FEC)
Starts: 01 October 1999 Ends: 30 September 2002 Value (£): 161,868
EPSRC Research Topic Classifications:
Image & Vision Computing
EPSRC Industrial Sector Classifications:
Healthcare No relevance to Underpinning Sectors
Related Grants:
Panel History:  
Summary on Grant Application Form
We have developed a neural network based scene classifier which labels the majority of objects found in natural scenes. This has been developed as an aid for low vision by presenting highly processed versions of the scenes to the severely visually impaired. The images display common objects (cars, roads, etc) in high contrast colours (user selectable) in which specific object types are always displayed in the same colour (e.g. all cars are yellow). A pilot study demonstrates a substantial improvement in scene understanding for low vision patients. Our current system is PC based and performs too slowly to allow real-time testing. The purpose of this proposal is to accelerate the system to allow such testing. The target platform will be an MPMP (Massively Parallel Media Processor) with 107 SHARC processors which was recently provided to the University under a HEFCE Joint Research Equipment Initiative. This system will support real-time testing of our techniques in a variety of indoor and outdoor environments allowing us to evaluate and refine our techniques as an aid to mobility using a structured series of patient tests. Furthermore, our industrial collaborator will provide a portable version of the same SHARC system before the end of the project.
Key Findings
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Summary
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Further Information:  
Organisation Website: http://www.bris.ac.uk