EPSRC Reference: |
GR/M31682/01 |
Title: |
RECOGNISING FACES FROM VIDEO: HUMAN & MACHINE CAPABILITIES |
Principal Investigator: |
Allinson, Professor NM |
Other Investigators: |
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Researcher Co-Investigators: |
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Project Partners: |
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Department: |
Electrical Engineering & Electronics |
Organisation: |
UMIST |
Scheme: |
Standard Research (Pre-FEC) |
Starts: |
01 October 1998 |
Ends: |
31 December 2001 |
Value (£): |
197,810
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EPSRC Research Topic Classifications: |
Cognitive Science Appl. in ICT |
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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 |
This proposal brings together leading experts in the fields of human face recognition and image engineering, to further the understanding of human abilities for face recognition from video sequences and to develop enhanced machine-based recognition systems for eventual applications such as security and surveillance. The closely integrated nature of this project, across such differing disciplines, is seen as one of its major features.Video-based face recognition has only recently become an active field for research, exploratory work in human video-based face recognition indicates a strong case for stored representation of identity which is not intrinsically linked to any single view of a face. Modelling these stored representations (using a variety of candidate compact representations), with an informed view of current and developing psychological evidence, will create advances in both disciplines. The work builds upon existing activities at each site. Integration across disciplines has been attempted rarely but has provided instructive insights for both machine and human vision researchers. The current status of both disciplines makes an integrated approach to video sequence studies particularly timely.Such work will lay solid foundations for the development of future practical recognition systems.
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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: |
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