2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), 2022
Yunho Choi, Hyeonchang Jeon, Sungha Lee, Isaac Han, Yiyue Luo, SeungJun Kim, Wojciech Matusik, Kyungjoong Kim
Natural movement is a challenging problem in virtual reality locomotion. However, existing foot-based locomotion methods lack naturalness due to physical limitations caused by wearing equipment. Therefore, in this study, we propose Seamless-walk, a novel virtual reality (VR) locomotion technique to enable locomotion in the virtual environment by walking on a high-resolution tactile carpet. The proposed Seamless-walk moves the user’s virtual character by extracting the users’ walking speed and orientation from raw tactile signals using machine learning techniques. We demonstrate that the proposed Seamless-walk is more natural and effective than existing VR locomotion methods by comparing them in VR game-playing tasks.