Human-AI Collaboration to Increase the Perception of VR

Abstract

Virtual reality (VR) is gaining popularity very fast due to newer solutions that increase user perception. Glasses, sensors, and treadmills are the basic functionality for immersing yourself in a virtual environment. In this paper, we propose a human-AI collaboration for analyzing the newly generated images that can be used for creating worlds. The presented method is based on analyzing different scenes (from simulation and real environment) using generative adversarial networks (GAN) and the communication with the user for assessments of the created new environment. User’s information contributes to the analysis of sample quality and possible rebuilding or retraining of the GAN model. The proposal increases the perception of VR by taking the user’s feelings in creating new environments. For this purpose, we combine GAN with fuzzy soft sets inference to gain the possibility of retraining/remodeling the used neural network. It was examined in theoretical simulation and real-environment case study.