Researchers at GIST have detailed the development of the VR locomotion system called ‘Seamless-walk’. It works in the following manner: the intelligent carpet captures high-resolution foot pressure imprints in real time as the user moves around by measuring the applied pressure through resistance changes. The footprint information is then fed into a machine learning model that extracts the strong pressure points using a technique called K-means clustering. In this method, the pressure points are divided into two clusters, corresponding to the user’s left and right feet. From these clusters, the user’s body direction and foot intervals are then extracted to estimate the angle and movement speed.
‘Seamless-walk’ has a modular structure that enables a scalable and inexpensive installation of a touch sensing platform. The team conducted tests on 80 individuals using Seamless-walk in a 3D virtual world exploration game, demonstrating that the novel technology of the system guarantees an immersive, natural, and comfortable experience. At the same time, it does not compromise the overall VR experience, outperforming existing VR locomotion methods. In the future, we plan to add more detailed gait analysis functions to the current system. This would enhance our sensor and gait analysis system to provide fall detection and health monitoring in a comfortable manner without any privacy issues.
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