Facial information can reveal the emotional status of individuals. Although traditional cameras can capture this information, such cameras struggle to acquire the necessary information in extreme lighting conditions. This thesis aim to investigate whether High Dynamic Range (HDR) imaging can capture human facial expression under complex lighting conditions, and in doing so, enhance Facial Expression Recognition (FER) performance. The techniques presented in this thesis focus on developing a baseline for images captured in scenes with harsh lighting conditions, where Low Dynamic Range (LDR) images have difficulty capturing the full range of light in a single exposure. The thesis considers unprocessed images and a variety of pre-processing methods to examine whether reducing the impact of large lighting variations could improve the quality of an input image. In addition, realistic facial data plays a key role in validating facial expression analysis systems. Today, the majority of FER algorithms are evaluated only on images generated in highly controlled laboratory environments. The variability of a facial appearance in an image could be dominated by changes in head pose and illumination conditions. This can effectively hide features that are necessary to discriminate different subjects or different facial articulations. New HDR imaging techniques are thus introduced to help ensure that all the details in a scene is captured no matter what the lighting conditions present, and all this detail is then available to the FER algorithms. This is also investigated on Face recognition algorithms.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:720471 |
| Date | January 2016 |
| Creators | Ige, Emmanuel |
| Publisher | University of Warwick |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://wrap.warwick.ac.uk/90327/ |
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