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Model of realism score for immersive VR systems

Abstract : A model of a realism score for immersive virtual reality and driving simulators is presented. First, we give an outlook of the different definitions of what ‘‘realism” is and the different approaches that exist in the literature to objectively quantify it. Then, we present the method, the theoretical development of the score and the results proposed. This realism score system aims to objectively quantify the characteristics of the visual perception happening for a perfect (non-altered vision) observer when experiencing an immersive VR system, as compared to the human visual system in a real (non-VR) situation. It addresses not only the visual perception but also the immersivity of the experience. The approach is different from the signal detection theory and the quantum efficiency theory that both rely on probabilities computation. It is made of several items, graded between 0 and 100, and divided in two sections: vision cues and immersion cues. These items represent, and are based on, the different skills of the human visual system. Realism score could be used as a helping tool in many applications such as objectively grading the performance of a VR system, defining the specifications of a new display, or choosing a simulator between several others available for a given experiment.
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Benoit Perroud, Stéphane Régnier, Andras Kemeny, Frédéric Merienne. Model of realism score for immersive VR systems. Transportation Research Part F: Traffic Psychology and Behaviour, 2017, pp.1-14. ⟨10.1016/j.trf.2017.08.015⟩. ⟨hal-01779643⟩

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