>Magister Scientiae - MSc / This research proposes an approach to recognizing facial expressions in the presence of
rotations and partial occlusions of the face. The research is in the context of automatic
machine translation of South African Sign Language (SASL) to English. The proposed
method is able to accurately recognize frontal facial images at an average accuracy of
75%. It also achieves a high recognition accuracy of 70% for faces rotated to 60◦. It was
also shown that the method is able to continue to recognize facial expressions even in
the presence of full occlusions of the eyes, mouth and left/right sides of the face. The
accuracy was as high as 70% for occlusion of some areas. An additional finding was that
both the left and the right sides of the face are required for recognition. As an addition,
the foundation was laid for a fully automatic facial expression recognition system that
can accurately segment frontal or rotated faces in a video sequence.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uwc/oai:etd.uwc.ac.za:11394/3367 |
| Date | January 2014 |
| Creators | Mushfieldt, Diego |
| Contributors | Ghaziasgar, Mehrdad, Connan, James |
| Publisher | University of Western Cape |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Rights | University of Western Cape |
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