Configurable Multi-agent Systems Based on Performance Matrix for Facial Recognition
Dr He Hongmei Lecturer in Software Engineering for Technical Computing

This event took place on 18th June 2014 at 11:30am (10:30 GMT)
Knowledge Media Institute, Berrill Building, The Open University, Milton Keynes, United Kingdom, MK7 6AA

In order to solve the intrapersonal variation problem in facial recognition, we propose a framework of a multi-engine system for facial recognition configurable in image types, watch sizes and engines based on performance matrices. The value of each cell in a performance matrix presents a confidence level for facial recognition; the quantified generalisation ability in a specific area of the performance matrix, corresponding to the pair of probe and training image variations, provides a reference for the selection of engines; and the cell value of a performance matrix at a specified size of watch list can be predicted through non-linear identification system approach using existing performance matrices for different sizes of watch lists. We demonstrated the improved performance of a system embedded with two engines, Eigenface and Local Binary Pattern Histograms algorithm.


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