Enhancing augmented vr interaction via egocentric scene analysis

Y Tian, CW Fu, S Zhao, R Li, X Tang, X Hu… - Proceedings of the ACM …, 2019 - dl.acm.org
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2019dl.acm.org
Augmented virtual reality (AVR) takes portions of the physical world into the VR world to
enable VR users to access physical objects. State-of-the-art solutions mainly focus on
extracting and showing physical objects in the VR world. In this work, we go beyond
previous solutions and propose a novel approach to realize AVR. We first analyze the
physical environment in the user's egocentric view through depth sensing and deep
learning, then acquire the layout and geometry of the surrounding objects, and further …
Augmented virtual reality (AVR) takes portions of the physical world into the VR world to enable VR users to access physical objects. State-of-the-art solutions mainly focus on extracting and showing physical objects in the VR world. In this work, we go beyond previous solutions and propose a novel approach to realize AVR. We first analyze the physical environment in the user's egocentric view through depth sensing and deep learning, then acquire the layout and geometry of the surrounding objects, and further explore their affordances. Based on the above information, we create visual guidance (hollowed guiding path) and hybrid user interfaces (augmented physical notepad, LR finger slider, and LRRL finger slider) to augment the AVR interaction. Empirical evaluations showed that the participants responded positively to our AVR techniques.
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