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Title: Facial feature processing using artificial neural networks
Author: Porter, Nicholas David
Awarding Body: University of Warwick
Current Institution: University of Warwick
Date of Award: 1998
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Describing a human face is a natural ability used in eveyday life. To the police, a witness description of a suspect is key evidence in the identification of the suspect. However, the process of examining "mug shots" to find a match to the description is tedious and often unfruitful. If a description could be stored with each photograph and used as a searchable index, this would provide a much more effective means of using "mug shots" for identification purposes. A set of descriptive measures have been defined by Shepherd [73] which seek to describe faces in a manner that may be used for just this purpose. This work investigates methods of automatically determining these descriptive measures from digitised images. Analysis is performed on the images to establish the potential for distinguishing between different categories in these descriptions. This reveals that while some of the classifications are relatively linear, others are very non-linear. Artificial neural networks (ANNs), being often used as non-linear classifiers, are considered as a means of automatically performing the classification of the images. As a comparison, simple linear classifiers are also applied to the same problems.
Supervisor: Not available Sponsor: Engineering and Physical Sciences Research Council ; Home Office
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry ; TA Engineering (General). Civil engineering (General) Pattern recognition systems Pattern perception Image processing Artificial intelligence