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IEEE VR2021顶会

Exploring Input Approximations for Control Panels in Virtual Reality

Markus Tatzgern, Christoph Birgmann

2021年份
7被引次数

摘要

Today's availability of sophisticated consumer-grade Virtual Reality (VR) hardware provides affordable access to training simulation technology. In contrast to more traditional high fidelity training simulations utilizing physical replicas of control panels that allow natural interaction, users of virtual training often rely on handheld VR controllers to manipulate simulated controls. Therefore, control manipulations of virtual buttons and sliders must be mapped to approximations of real hand manipulations. For instance, the turning of a physical knob with thumb and index finger can be mapped to a gross motor forearm rotation, or a fine motor joystick manipulation when manipulating a controller. In this paper, we present an exploration of hand input approximations of real hands to manipulate the buttons, toggles, knobs and sliders using typical handheld VR controllers. We use common Oculus Quest controllers that rely on capacitive sensing to create basic, approximate hand gestures. We demonstrate the potential of our designs by performing an experiment in which we compare approximate hand gestures against using the controller's joystick that allows fine motor control using thumb input, and a baseline ray-casting interaction that is commonly used in VR applications. We provide a detailed analysis of our interaction designs using the Framework for Interactive Fidelity Analysis (FIFA), which allows us to discuss differences between input approximations and the real-world hand manipulations.

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