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    A Calibrated Olfactory Display for High Fidelity Virtual Environments
    (The Eurographics Association, 2016) Dhokia, Amar; Doukakis, Efstratious; Asadipour, Ali; Harvey, Carlo; Bashford-Rogers, Thomas; Debattista, Kurt; Waterfield, Brian; Chalmers, Alan; Cagatay Turkay and Tao Ruan Wan
    Olfactory displays provide a means to reproduce olfactory stimuli for use in virtual environments. Many of the designs produced by researchers, strive to provide stimuli quickly to users and focus on improving usability and portability, yet concentrate less on providing high levels of accuracy to improve the fidelity of odour delivery. This paper provides the guidance to build a reproducible and low cost olfactory display which is able to provide odours to users in a virtual environment at accurate concentration levels that are typical in everyday interactions; this includes ranges of concentration below parts per million and into parts per billion. This paper investigates build concerns of the olfactometer and its proper calibration in order to ensure concentration accuracy of the device. An analysis is provided on the recovery rates of a specific compound after excitation. This analysis provides insight into how this result can be generalisable to the recovery rates of any volatile organic compound, given knowledge of the specific vapour pressure of the compound.
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    Selective BRDFs for High Fidelity Rendering
    (The Eurographics Association, 2016) Bradley, Tim; Debattista, Kurt; Bashford-Rogers, Thomas; Harvey, Carlo; Doukakis, Stratos; Chalmers, Alan; Cagatay Turkay and Tao Ruan Wan
    High fidelity rendering systems rely on accurate material representations to produce a realistic visual appearance. However, these accurate models can be slow to evaluate. This work presents an approach for approximating these high accuracy reflectance models with faster, less complicated functions in regions of an image which possess low visual importance. A subjective rating experiment was conducted in which thirty participants were asked to assess the similarity of scenes rendered with low quality reflectance models, a high quality data-driven model and saliency based hybrids of those images. In two out of the three scenes that were evaluated significant differences were not found between the hybrid and reference images. This implies that in less visually salient regions of an image computational gains can be achieved by approximating computationally expensive materials with simpler analytic models.
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    Exploring Face Recognition under Complex Lighting Conditions with HDR Imaging
    (The Eurographics Association, 2016) Ige, Emmanuel O.; Debattista, Kurt; Muhkerjee, Ratnajit; Chalmers, Alan; Cagatay Turkay and Tao Ruan Wan
    Applying image processing applications under complex or harsh lighting conditions can be a difficult challenge. In particular, face recognition can be prone to such limitations due to the uncontrolled nature of the applications to which it is applied. One of the conventional ways used to resolve this concern is by capturing images under controlled light or pre-processing the affected images, which can change the perception of the resultant images. One of the primary issues with this is the lack of information present in the original images due to over-exposed and under-exposed pixels. High Dynamic Range (HDR) imaging offers an alternative due to its capability of handling natural lighting. This paper explores the use HDR imaging for face recognition. A training and testing set of HDR images under different harsh lighting conditions was created. Traditional low dynamic range methods were compared with using the full range and applying HDR methods to a traditional face recognition method. Results demonstrate that adapting HDR captured images for use with traditional face recognition methods via a tone mapping provides sufficient improvement and enables traditional algorithms to cope well with harsh lighting scenarios.