70 research outputs found

    Human Centric Facial Expression Recognition

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    Facial expression recognition (FER) is an area of active research, both in computer science and in behavioural science. Across these domains there is evidence to suggest that humans and machines find it easier to recognise certain emotions, for example happiness, in comparison to others. Recent behavioural studies have explored human perceptions of emotion further, by evaluating the relative contribution of features in the face when evaluating human sensitivity to emotion. It has been identified that certain facial regions have more salient features for certain expressions of emotion, especially when emotions are subtle in nature. For example, it is easier to detect fearful expressions when the eyes are expressive. Using this observation as a starting point for analysis, we similarly examine the effectiveness with which knowledge of facial feature saliency may be integrated into current approaches to automated FER. Specifically, we compare and evaluate the accuracy of ‘full-face’ versus upper and lower facial area convolutional neural network (CNN) modelling for emotion recognition in static images, and propose a human centric CNN hierarchy which uses regional image inputs to leverage current understanding of how humans recognise emotions across the face. Evaluations using the CK+ dataset demonstrate that our hierarchy can enhance classification accuracy in comparison to individual CNN architectures, achieving overall true positive classification in 93.3% of cases

    Motor signatures of emotional reactivity in frontotemporal dementia

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    Automatic motor mimicry is essential to the normal processing of perceived emotion, and disrupted automatic imitation might underpin socio-emotional deficits in neurodegenerative diseases, particularly the frontotemporal dementias. However, the pathophysiology of emotional reactivity in these diseases has not been elucidated. We studied facial electromyographic responses during emotion identification on viewing videos of dynamic facial expressions in 37 patients representing canonical frontotemporal dementia syndromes versus 21 healthy older individuals. Neuroanatomical associations of emotional expression identification accuracy and facial muscle reactivity were assessed using voxel-based morphometry. Controls showed characteristic profiles of automatic imitation, and this response predicted correct emotion identification. Automatic imitation was reduced in the behavioural and right temporal variant groups, while the normal coupling between imitation and correct identification was lost in the right temporal and semantic variant groups. Grey matter correlates of emotion identification and imitation were delineated within a distributed network including primary visual and motor, prefrontal, insular, anterior temporal and temporo-occipital junctional areas, with common involvement of supplementary motor cortex across syndromes. Impaired emotional mimesis may be a core mechanism of disordered emotional signal understanding and reactivity in frontotemporal dementia, with implications for the development of novel physiological biomarkers of socio-emotional dysfunction in these diseases

    Aging and the neuroeconomics of decision making: A review

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    Morphology, Life History and Identification of Sex Pheromone Components of an Undescribed Species of Choristoneura (Lepidoptera: Tortricidae) on Scots Pine in British Columbia

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    The morphology and life history of a probable new species of tortricid on Scots pine in British Columbia is described. It differs from other Canadian pine feeding Choristoneura. Abdominal tip extracts of unmated females contained Z-11- and E-11-tetradecenyl acetates and alcohols. An equal mixture of these materials was an effective attractant for capturing males in delta traps and is recommended for the detection and monitoring of this insect
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