Enhancing Augmented VR Interaction via Egocentric Scene Analysis

PubDate: September 2019

Teams: The Chinese University of Hong Kong，National University of Singapore

Writers: Yang Tian；Chi-Wing Fu；Shengdong Zhao；Ruihui Li；Xiao Tang；Xiaowei Hu；Pheng-Ann Heng

PDF: Enhancing Augmented VR Interaction via Egocentric Scene Analysis

Abstract

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.