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This thesis examines the role of emotion in face recognition, using measures of the visual scanpath as indicators of recognition. There are two key influences of emotion in face recognition: the emotional expression displayed upon a face, and the emotional feelings evoked within a perceiver in response to a familiar person. An initial set of studies examined these processes in healthy participants. First, positive emotional expressions were found to facilitate the processing of famous faces, and negative expressions facilitated the processing of novel faces. A second set of studies examined the role of emotional feelings in recognition. Positive feelings towards a face were also found to facilitate processing, in both an experimental study using newly learned faces and in the recognition of famous faces. A third set of studies using healthy participants examined the relative influences of emotional expression and emotional feelings in face recognition. For newly learned faces, positive expressions and positive feelings had a similar influence in recognition, with no presiding role of either dimension. However, emotional feelings had an influence over and above that of expression in the recognition of famous faces. A final study examined whether emotional valence could influence covert recognition in developmental prosopagnosia, and results suggested the patients process faces according to emotional valence rather than familiarity per se. Specifically, processing was facilitated for studied-positive faces compared to studied-neutral and novel faces, but impeded for studied-negative faces. This pattern of findings extends existing reports of a positive-facilitation effect in face recognition, and suggests there may be a closer relationship between facial familiarity and emotional valence than previously envisaged. The implications of these findings are discussed in relation to models of normal face recognition and theories of covert recognition in prosopagnosia.

Due to the recent advances in visual communication and face recognition technologies, automatic face detection has attracted a great deal of research interest. Being a diverse problem, the development of face detection research has comprised contributions from researchers in various fields of sciences. This thesis examines the fundamentals of various face detection techniques implemented since the early 70's. Two groups of techniques are identified based on their approach in applying face knowledge as a priori: feature-based and image-based. One of the problems faced by the current feature-based techniques, is the lack of costeffective segmentation algorithms that are able to deal with issues such as background and illumination variations. As a result a novel facial feature segmentation algorithm is proposed in this thesis. The algorithm aims to combine spatial and temporal information using low cost techniques. In order to achieve this, an existing motion detection technique is analysed and implemented with a novel spatial filter, which itself is proved robust for segmentation of features in varying illumination conditions. Through spatio-temporal information fusion, the algorithm effectively addresses the background and illumination problems among several head and shoulder sequences. Comparisons of the algorithm with existing motion and spatial techniques establishes the efficacy of the combined approach.

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It has often been argued that the processing of faces is 'special' relative to the processing of other objects and there is much evidence in support of this notion. One source of evidence is the inversion effect, which occurs when faces presented upright are recognised significantly better than faces presented upside down. This effect of stimulus inversion has been shown to impair face recognition to a greater extent than for any other object class. It is this disproportionate effect that has been given as one source of evidence that face processing is special. However, other research has argued that effects of inversion can be found for non-face stimuli providing that there is sufficient development of expertise with them and that these stimuli can be defined by a common prototype. This thesis further explores this idea. Inversion effects were investigated for both prototypically and non-prototypically defined, abstract, chequerboard stimuli and compared with those for faces. When subjects learned to categorise chequerboard stimuli that were defined by a common prototype equal size inversion effects were found to those observed for faces. However, inversion effects were not observed for category training with multiple exemplars of chequerboard stimuli that were not defined by a common prototype. Together the findings are consistent with the idea that inversion effects are a general phenomenon resulting from the acquisition of category expertise with any prototype defined stimulus category. They undermine the inversion effect as a source of evidence for the specialness of face processing. Further, using a new Moving Windows technique, additional experiments investigated the underlying mechanisms responsible for the effects of inversion found for faces and chequerboards. These showed that the diagnostic image regions searched differ across the two stimulus classes. However, on the basis of the results, it is argued that the inversion effects found for both could result from impaired processing of second-order configural information.

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