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Dense surface models of the human face

Hutton, Tim J.; (2004) Dense surface models of the human face. Doctoral thesis, UCL (University College London). Green open access

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Abstract

This thesis describes and evaluates Dense Surface Models (DSMs), a new technique for building point distribution models of surfaces, from raw input data. DSMs can be used on data from a wide range of surface acquisition systems without preprocessing since they do not require that the surfaces be closed or even locally manifold, and can cope well with holes and spikes in the surfaces. This is an advantage over comparable techniques, which impose such constraints on the input. The core of the DSM algorithm is as follows. A dense correspondence is made between the surfaces using thin-plate spline warping guided by means of a small set of hand-placed landmarks. The area of interest is automatically defined by a threshold on a measure of the closeness of the correspondence at each point. A point distribution model is then built using the vertices from the trimmed and densely-corresponded surfaces. The key benefit of using models of the whole surface is illustrated by the large improvement in classification on face shape that is obtained when using DSMs as compared to landmark-based geometric morphometrics. This is demonstrated by testing classification by gender and also by congenital anomaly where facial growth and form is abnormal. The latter is currently the primary application of DSMs. The use of DSMs for automatically fitting to new scans is evaluated for robustness and accuracy. Methods for analyzing continuous and discrete parameters such as age and gender are presented and evaluated. The incorporation of grey-level information with the shape information is also possible, and is explored.

Type: Thesis (Doctoral)
Title: Dense surface models of the human face
Identifier: PQ ETD:602535
Open access status: An open access version is available from UCL Discovery
Language: English
Additional information: Thesis digitised by ProQuest. Third party copyright material has been removed from the ethesis. Images identifying individuals have been redacted or partially redacted to protect their identity.
UCL classification: UCL > School of Life and Medical Sciences > Faculty of Medical Sciences > Eastman Dental Institute
URI: http://discovery.ucl.ac.uk/id/eprint/1446610
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